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PHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building A DAY IN THE LIFE OF A PHD STUDENT A Day in the Life of a PhD Student. 26th March 2021. My name is Faysal and I am a second year PhD student at the Centre for Doctoral Training in Smart Medical Imaging at King’s College London and Imperial College London. The aim of my PhD project, supervised by Prof Mark Green (King’s College London) and Dr James Wilton-Ely (Imperial TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with MULTI-TRANSMIT TECHNOLOGY FOR OPTIMAL MAGNETIC RESONANCE 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Alexander Hammers, King’s College London There are increasing numbers of procedures in which electrodes are placed at depth in the human brain – both for recording and stimulation. While implanted electrode recordings are used in epilepsy treatment, DBS is INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array REAL-TIME ASSESSMENT OF CORONARY HAEMODYNAMICS VIA HYBRID 1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be applied under real-time interventional settings. To achieve this, a combination of computational fluid dynamics and machine learning HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects.PHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building A DAY IN THE LIFE OF A PHD STUDENT A Day in the Life of a PhD Student. 26th March 2021. My name is Faysal and I am a second year PhD student at the Centre for Doctoral Training in Smart Medical Imaging at King’s College London and Imperial College London. The aim of my PhD project, supervised by Prof Mark Green (King’s College London) and Dr James Wilton-Ely (Imperial TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with MULTI-TRANSMIT TECHNOLOGY FOR OPTIMAL MAGNETIC RESONANCE 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Alexander Hammers, King’s College London There are increasing numbers of procedures in which electrodes are placed at depth in the human brain – both for recording and stimulation. While implanted electrode recordings are used in epilepsy treatment, DBS is INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array REAL-TIME ASSESSMENT OF CORONARY HAEMODYNAMICS VIA HYBRID 1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be applied under real-time interventional settings. To achieve this, a combination of computational fluid dynamics and machine learning APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPARTNERSHIPS
Partnerships. Partnership with industry is essential to the success of the CDT. It enables translation of our research and strengthens our understanding of the commercial challenges in the medical imaging sector. There are many different ways for companies of all sizes and specialisms within the field to collaborate with the CDT. EXPLORING THE INNER WORLD THROUGH A VIRTUAL WORLD Figure 1: The MR compatible Virtual Reality system which will be used in the project in use. It consists of a MR compatible projector which is placed on the examination table which enters the scanner bore and a VR headset mounted on the receive head coil. There is a pair of infrared cameras integrated into the headset which can precisely track AI BASED MULTI-ORGAN SEGMENTATION OF HEALTHY TISSUE 1st Supervisor: Paul Marsden, King’s College London2nd Supervisor: Julia Schnabel, King’s College LondonClinical Champion: Malene Fisher, King’s College London Aim of the PhD Project: Design and optimisation of AI tools suitable for segmentation of multiple organs. Co-registration and feature learning from both CT and PET data within these tools. Combining the above into one multi-organ REAL-TIME ASSESSMENT OF CORONARY HAEMODYNAMICS VIA HYBRID 1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be applied under real-time interventional settings. To achieve this, a combination of computational fluid dynamics and machine learning MONITORING BLOOD GLUCOSE LEVELS WITH IMAGING 1st supervisor: Jordi Alastruey, King’s College London2nd supervisor: Pablo Lamata, King’s College LondonClinical Champion: Phil ChowienczykIndustry Supervisor: John Dennis and Masih Nilchian Aim of the PhD Project: ~10% world population has to monitor daily their glucose level (GL) due to diabetes. Accurate GL monitoring involves finger-pricking, which is invasive, painful, time-consuming DEEP-LEARNING PET-MR LONGITUDINAL RECONSTRUCTION FOR LOWER 1st Supervisor: Andrew Reader, King’s College London2nd Supervisor: Andy King, King’s College LondonClinical Champions: Vicky Goh and Gary Cook, King’s College London Aim of the PhD Project: This project explores new synergistic multi-modality data with an emphasis on AI-enhanced PET-MR image reconstruction methods, exploiting AI to improve imaging capabilities for cancer treatment FUNCTIONAL IMAGING OF LIVER USING CONTRAST-ENHANCED This is an industrial PhD project aimed at developing novel imaging techniques for contrast-enhanced liver imaging using the ultrasound contrast agent (UCA) SonazoidTM. UCAs are micrometer size bubbles (with the size range of 3-10 µm diameters) that consist of an inert gas core encapsulated by a stabilizing shell (protein, lipid orpolymer).
A NEW WINDOW INTO THE UTERUS TO VISUALISE FETAL LIPID 1st Supervisor: Enrico De Vita, King’s College London2nd Supervisor: Po-Wah So, King’s College LondonClinical Champions: Catherine Williamson and Mary Rutherford, King’s College LondonAdditional Supervisors: Jo Hajnal and Jana Hutter, King’s College London Aim of the PhD Project: Development of a novel non-invasive robust and reliable MRI and MR Spectroscopy methodology, incorporating HOME - EPSRC CDT IN SMART MEDICAL IMAGING Having reopened our recruitment for the 2021/22 academic year, we are pleased to announce that we are holding a virtual application clinic between 4pm-5pm GMT on 30 March, where CDT staff and students will be on hand to answer prospective applicants’ questions about the application process, including those concerning filling out theapplication form.
PHD PROGRAMMES
Whether it is through attendance as a delegate, speaking or organisation committee membership, involvement in conferences is an integral part of our students’ experience. APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Who should apply? Medical Imaging is a broad and diverse research area with students from a diverse range of backgrounds. Applicants will normally be expected to have first class, high upper second or Distinction degrees in any of the following subjects: THE CARDIAC DIGITAL TWIN 1st Supervisor: Steven Niederer, King’s College London 2nd Supervisor: Alistair Young, King’s College London Clinical Champion: Aldo Rinaldi, King’s College London Aim of the PhD Project: Imaging cardiac function, form and physiology through time Automatically quantify shape and function with uncertainty form cardiac images. Implement a Bayesian update for images to integrate A DAY IN THE LIFE OF A PHD STUDENT It wouldn’t be an ordinary day without taking part in a Zoom call and almost instinctively asking the question “Can you hear me?”. As is such, I tuned in (or zoomed in?) for a group meeting at around 7:30 pm with Somali Academics to discuss our plans for the rest of the year. The lockdown has affected many students and in particular students from ethnic minority backgrounds, so we TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with AI BASED MULTI-ORGAN SEGMENTATION OF HEALTHY TISSUE 1st Supervisor: Paul Marsden, King’s College London2nd Supervisor: Julia Schnabel, King’s College LondonClinical Champion: Malene Fisher, King’s College London Aim of the PhD Project: Design and optimisation of AI tools suitable for segmentation of multiple organs. Co-registration and feature learning from both CT and PET data within these tools. Combining the above into one multi-organ ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with REAL-TIME ASSESSMENT OF CORONARY HAEMODYNAMICS VIA HYBRID 1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be applied under real-time interventional settings. To achieve this, a combination of computational fluid dynamics and machine learning HOME - EPSRC CDT IN SMART MEDICAL IMAGING Having reopened our recruitment for the 2021/22 academic year, we are pleased to announce that we are holding a virtual application clinic between 4pm-5pm GMT on 30 March, where CDT staff and students will be on hand to answer prospective applicants’ questions about the application process, including those concerning filling out theapplication form.
PHD PROGRAMMES
Whether it is through attendance as a delegate, speaking or organisation committee membership, involvement in conferences is an integral part of our students’ experience. APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Who should apply? Medical Imaging is a broad and diverse research area with students from a diverse range of backgrounds. Applicants will normally be expected to have first class, high upper second or Distinction degrees in any of the following subjects: THE CARDIAC DIGITAL TWIN 1st Supervisor: Steven Niederer, King’s College London 2nd Supervisor: Alistair Young, King’s College London Clinical Champion: Aldo Rinaldi, King’s College London Aim of the PhD Project: Imaging cardiac function, form and physiology through time Automatically quantify shape and function with uncertainty form cardiac images. Implement a Bayesian update for images to integrate A DAY IN THE LIFE OF A PHD STUDENT It wouldn’t be an ordinary day without taking part in a Zoom call and almost instinctively asking the question “Can you hear me?”. As is such, I tuned in (or zoomed in?) for a group meeting at around 7:30 pm with Somali Academics to discuss our plans for the rest of the year. The lockdown has affected many students and in particular students from ethnic minority backgrounds, so we TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with AI BASED MULTI-ORGAN SEGMENTATION OF HEALTHY TISSUE 1st Supervisor: Paul Marsden, King’s College London2nd Supervisor: Julia Schnabel, King’s College LondonClinical Champion: Malene Fisher, King’s College London Aim of the PhD Project: Design and optimisation of AI tools suitable for segmentation of multiple organs. Co-registration and feature learning from both CT and PET data within these tools. Combining the above into one multi-organ ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with REAL-TIME ASSESSMENT OF CORONARY HAEMODYNAMICS VIA HYBRID 1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be applied under real-time interventional settings. To achieve this, a combination of computational fluid dynamics and machine learning RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines and many research projects bridge across more than one theme. EXPLORING THE INNER WORLD THROUGH A VIRTUAL WORLD 1st supervisor: Tomoki Arichi, King’s College London2nd supervisor: Jo Hajnal, King’s College LondonAdditional supervisor: Bernhard Kainz, Imperial College London Aim of the PhD Project: Develop a fully integrated immersive Virtual Reality (VR) experience in the MRI scanner. Integrate multi-modal sensory and physiological information into the VR experience to establish a new level of VRPARTNERSHIPS
Radhouene Neji, Senior Key Expert and Collaboration Manager for Magnetic Resonance at Siemens Healthineers: Siemens is involved with the EPSRC CDT in Smart Medical Imaging in various different ways, including sponsorship of several studentships, technology provision for research and, as one of Siemens’ imaging collaboration scientists based here at King’s, I myself am heavily involved with REAL-TIME ASSESSMENT OF CORONARY HAEMODYNAMICS VIA HYBRID 1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be applied under real-time interventional settings. To achieve this, a combination of computational fluid dynamics and machine learning AI BASED MULTI-ORGAN SEGMENTATION OF HEALTHY TISSUE 1st Supervisor: Paul Marsden, King’s College London2nd Supervisor: Julia Schnabel, King’s College LondonClinical Champion: Malene Fisher, King’s College London Aim of the PhD Project: Design and optimisation of AI tools suitable for segmentation of multiple organs. Co-registration and feature learning from both CT and PET data within these tools. Combining the above into one multi-organ AI-ENABLED ASSESSMENT OF CARDIAC FUNCTION FROM 1st Supervisor: Andrew King, King’s College London 2nd Supervisor: Miaojing Shi, King’s College London Additional Supervisor: Esther Puyol, King’s College London Clinical Champion: Bram Ruijsink, King’s College London Aim of the PhD Project: Develop deep learning techniques for automated interpretation of echocardiography images and train/evaluate them using large-scale datasets DEEP-LEARNING PET-MR LONGITUDINAL RECONSTRUCTION FOR LOWER 1st Supervisor: Andrew Reader, King’s College London2nd Supervisor: Andy King, King’s College LondonClinical Champions: Vicky Goh and Gary Cook, King’s College London Aim of the PhD Project: This project explores new synergistic multi-modality data with an emphasis on AI-enhanced PET-MR image reconstruction methods, exploiting AI to improve imaging capabilities for cancer treatment MONITORING BLOOD GLUCOSE LEVELS WITH IMAGING 1st supervisor: Jordi Alastruey, King’s College London2nd supervisor: Pablo Lamata, King’s College LondonClinical Champion: Phil ChowienczykIndustry Supervisor: John Dennis and Masih Nilchian Aim of the PhD Project: ~10% world population has to monitor daily their glucose level (GL) due to diabetes. Accurate GL monitoring involves finger-pricking, which is invasive, painful, time-consuming FUNCTIONAL IMAGING OF LIVER USING CONTRAST-ENHANCED 1st Supervisor: Mengxing Tang, Imperial College London2nd Supervisor: Kirsten Christensen Jeffries, King’s College LondonIndustry Supervisor: Ying Luan Project Description / Background: This is an industrial PhD project aimed at developing novel imaging techniques for contrast-enhanced liver imaging using the ultrasound contrast agent (UCA) SonazoidTM. UCAs are micrometer size bubbles (with A NEW WINDOW INTO THE UTERUS TO VISUALISE FETAL LIPID 1st Supervisor: Enrico De Vita, King’s College London2nd Supervisor: Po-Wah So, King’s College LondonClinical Champions: Catherine Williamson and Mary Rutherford, King’s College LondonAdditional Supervisors: Jo Hajnal and Jana Hutter, King’s College London Aim of the PhD Project: Development of a novel non-invasive robust and reliable MRI and MR Spectroscopy methodology, incorporating HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
PEOPLE - EPSRC CDT IN SMART MEDICAL IMAGING Prof Gary Cook is Professor of PET Imaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London. He trained in radiology and then nuclear medicine in London. He is a clinical academic in the Cancer Imaging Department, BMEIS, KCL and an honorary consultant at Guy’s & St Thomas’ Hospitals.PARTNERSHIPS
Partnerships. Partnership with industry is essential to the success of the CDT. It enables translation of our research and strengthens our understanding of the commercial challenges in the medical imaging sector. There are many different ways for companies of all sizes and specialisms within the field to collaborate with the CDT. TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with CARDIAC MULTIPARAMETRIC MAGNETIC RESONANCE FINGERPRINTING 1st supervisor: Claudia Prieto, King’s College London 2nd supervisor: Daniel Rueckert, Imperial College London Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality in the Western world, causing over 65.000 deaths every year in England. Magnetic Resonance Imaging (MRI) is a very promising non-invasive tool for early risk assessment, guidance of therapy 3D CARDIAC MAGNETIC RESONANCE FINGERPRINTING WITH DEEP 3D cardiac magnetic resonance fingerprinting with deep learning. Magnetic Resonance Imaging (MRI) has become an important non-invasive tool for risk assessment and treatment monitoring of cardiovascular disease. Conventional MR images are qualitative measurements that depend on different parameters such as the longitudinal T1 and thetransverse
AI ENABLED MOTION CORRECTED QUANTITATIVE MRI OF THE FETAL 1st Supervisor: Jo Hajnal, King’s College London2nd Supervisor: Daniel Rueckert, Imperial College LondonClinical Champion: Mary Rutherford, King’s College LondonIndustry Supervisor: Johan van den Brink and Maarten Versluis Aim of the PhD Project: During the second half of pregnancy the human brain undergoes exuberant growth, with both microscopic and macropic changes happening rapidly. In MULTI-TRANSMIT TECHNOLOGY FOR OPTIMAL MAGNETIC RESONANCE 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Alexander Hammers, King’s College London There are increasing numbers of procedures in which electrodes are placed at depth in the human brain – both for recording and stimulation. While implanted electrode recordings are used in epilepsy treatment, DBS is HOW DO MEDICAL IMAGING RADIOISOTOPES USED FOR DIAGNOSTIC 1st supervisor: Samantha Terry, King’s College London 2nd supervisor: Gilbert Fruhwirth, King’s College London Aim of the PhD Project: Molecular imaging with radionuclides can pinpoint disease locations and measure changes in metabolism and gene expression. Also, reporter gene imaging has long been used to monitor cellular processes but has only recently been used with radionuclides ONE-STEP, SITE-SPECIFIC LABELLING OF HIS-TAGGED PROTEINS 1st Supervisor: Phil Blower, King’s College London2nd Supervisor: Michelle Ma, King’s College London Clinical Champion: Gary Cook, King’s College LondonIndustry Supervisor: Levente Meszaros Aim of the PhD Project:The project will combine new transition metal chemistry with protein engineering to produce and evaluate preclinically (in vitro, in vivo) a theranostic pair of HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
PEOPLE - EPSRC CDT IN SMART MEDICAL IMAGING Prof Gary Cook is Professor of PET Imaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London. He trained in radiology and then nuclear medicine in London. He is a clinical academic in the Cancer Imaging Department, BMEIS, KCL and an honorary consultant at Guy’s & St Thomas’ Hospitals.PARTNERSHIPS
Partnerships. Partnership with industry is essential to the success of the CDT. It enables translation of our research and strengthens our understanding of the commercial challenges in the medical imaging sector. There are many different ways for companies of all sizes and specialisms within the field to collaborate with the CDT. TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with CARDIAC MULTIPARAMETRIC MAGNETIC RESONANCE FINGERPRINTING 1st supervisor: Claudia Prieto, King’s College London 2nd supervisor: Daniel Rueckert, Imperial College London Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality in the Western world, causing over 65.000 deaths every year in England. Magnetic Resonance Imaging (MRI) is a very promising non-invasive tool for early risk assessment, guidance of therapy 3D CARDIAC MAGNETIC RESONANCE FINGERPRINTING WITH DEEP 3D cardiac magnetic resonance fingerprinting with deep learning. Magnetic Resonance Imaging (MRI) has become an important non-invasive tool for risk assessment and treatment monitoring of cardiovascular disease. Conventional MR images are qualitative measurements that depend on different parameters such as the longitudinal T1 and thetransverse
AI ENABLED MOTION CORRECTED QUANTITATIVE MRI OF THE FETAL 1st Supervisor: Jo Hajnal, King’s College London2nd Supervisor: Daniel Rueckert, Imperial College LondonClinical Champion: Mary Rutherford, King’s College LondonIndustry Supervisor: Johan van den Brink and Maarten Versluis Aim of the PhD Project: During the second half of pregnancy the human brain undergoes exuberant growth, with both microscopic and macropic changes happening rapidly. In MULTI-TRANSMIT TECHNOLOGY FOR OPTIMAL MAGNETIC RESONANCE 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Alexander Hammers, King’s College London There are increasing numbers of procedures in which electrodes are placed at depth in the human brain – both for recording and stimulation. While implanted electrode recordings are used in epilepsy treatment, DBS is HOW DO MEDICAL IMAGING RADIOISOTOPES USED FOR DIAGNOSTIC 1st supervisor: Samantha Terry, King’s College London 2nd supervisor: Gilbert Fruhwirth, King’s College London Aim of the PhD Project: Molecular imaging with radionuclides can pinpoint disease locations and measure changes in metabolism and gene expression. Also, reporter gene imaging has long been used to monitor cellular processes but has only recently been used with radionuclides ONE-STEP, SITE-SPECIFIC LABELLING OF HIS-TAGGED PROTEINS 1st Supervisor: Phil Blower, King’s College London2nd Supervisor: Michelle Ma, King’s College London Clinical Champion: Gary Cook, King’s College LondonIndustry Supervisor: Levente Meszaros Aim of the PhD Project:The project will combine new transition metal chemistry with protein engineering to produce and evaluate preclinically (in vitro, in vivo) a theranostic pair of HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project HOME - EPSRC CDT IN SMART MEDICAL IMAGING Having reopened our recruitment for the 2021/22 academic year, we are pleased to announce that we are holding a virtual application clinic between 4pm-5pm GMT on 30 March, where CDT staff and students will be on hand to answer prospective applicants’ questions about the application process, including those concerning filling out theapplication form.
LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines and APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application.PHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
PEOPLE - EPSRC CDT IN SMART MEDICAL IMAGING Prof Gary Cook is Professor of PET Imaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London. He trained in radiology and then nuclear medicine in London. He is a clinical academic in the Cancer Imaging Department, BMEIS, KCL and an honorary consultant at Guy’s & St Thomas’ Hospitals.PARTNERSHIPS
Partnerships. Partnership with industry is essential to the success of the CDT. It enables translation of our research and strengthens our understanding of the commercial challenges in the medical imaging sector. There are many different ways for companies of all sizes and specialisms within the field to collaborate with the CDT. 3D CARDIAC MAGNETIC RESONANCE FINGERPRINTING WITH DEEP 3D cardiac magnetic resonance fingerprinting with deep learning. Magnetic Resonance Imaging (MRI) has become an important non-invasive tool for risk assessment and treatment monitoring of cardiovascular disease. Conventional MR images are qualitative measurements that depend on different parameters such as the longitudinal T1 and thetransverse
CARDIAC MULTIPARAMETRIC MAGNETIC RESONANCE FINGERPRINTING 1st supervisor: Claudia Prieto, King’s College London 2nd supervisor: Daniel Rueckert, Imperial College London Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality in the Western world, causing over 65.000 deaths every year in England. Magnetic Resonance Imaging (MRI) is a very promising non-invasive tool for early risk assessment, guidance of therapy MULTI-TRANSMIT TECHNOLOGY FOR OPTIMAL MAGNETIC RESONANCE 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Alexander Hammers, King’s College London There are increasing numbers of procedures in which electrodes are placed at depth in the human brain – both for recording and stimulation. While implanted electrode recordings are used in epilepsy treatment, DBS is AI ENABLED MOTION CORRECTED QUANTITATIVE MRI OF THE FETAL 1st Supervisor: Jo Hajnal, King’s College London2nd Supervisor: Daniel Rueckert, Imperial College LondonClinical Champion: Mary Rutherford, King’s College LondonIndustry Supervisor: Johan van den Brink and Maarten Versluis Aim of the PhD Project: During the second half of pregnancy the human brain undergoes exuberant growth, with both microscopic and macropic changes happening rapidly. In MONITORING BLOOD GLUCOSE LEVELS WITH IMAGING 1st supervisor: Jordi Alastruey, King’s College London2nd supervisor: Pablo Lamata, King’s College LondonClinical Champion: Phil ChowienczykIndustry Supervisor: John Dennis and Masih Nilchian Aim of the PhD Project: ~10% world population has to monitor daily their glucose level (GL) due to diabetes. Accurate GL monitoring involves finger-pricking, which is invasive, painful, time-consuming HOW DO MEDICAL IMAGING RADIOISOTOPES USED FOR DIAGNOSTIC 1st supervisor: Samantha Terry, King’s College London 2nd supervisor: Gilbert Fruhwirth, King’s College London Aim of the PhD Project: Molecular imaging with radionuclides can pinpoint disease locations and measure changes in metabolism and gene expression. Also, reporter gene imaging has long been used to monitor cellular processes but has only recently been used with radionuclides ONE-STEP, SITE-SPECIFIC LABELLING OF HIS-TAGGED PROTEINS 1st Supervisor: Phil Blower, King’s College London2nd Supervisor: Michelle Ma, King’s College London Clinical Champion: Gary Cook, King’s College LondonIndustry Supervisor: Levente Meszaros Aim of the PhD Project:The project will combine new transition metal chemistry with protein engineering to produce and evaluate preclinically (in vitro, in vivo) a theranostic pair of HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project HOME - EPSRC CDT IN SMART MEDICAL IMAGING WORLD-LEADING Research. Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging. Available Projects. LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGING Next steps. Select the programme to apply to: under Programme Name select ‘Biomedical Engineering and Imaging Science Research MPhil/PhD (Full-time)’. Once the programme has been selected, please select the start date (01 October 2021) and read the on-screen information about how to progress through the application. RESEARCH - EPSRC CDT IN SMART MEDICAL IMAGING Research Themes. Through our research, we are looking to build smart new technologies into the entire medical imaging process. We have four themes, which our students’ projects are all directed towards. Each theme crosses multiple academic disciplines andPHD PROGRAMMES
Programme structure. Over their four years of study within the CDT, we aim to equip all of our students with the skills and knowledge that will enable the to explore a range of career options after their PhD. CDT students normally follow a 1+3 pathway. In their first year, they typically join a cohort of around 15 to study for a Masters of THE CARDIAC DIGITAL TWIN A digital twin is a digital replica of a specific physical entity. It encodes physics, physiology, population data and patient specific measurements and combines these with AI techniques for updating and interrogating the model. Healthcare is the industry most likely to be disrupted by the digital twin technology, as it enables building INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with ENGINEERING WHOLE-BODY 7 TESLA MRI COIL FOR SIGNAL 1st Supervisor: Özlem Ipek, King’s College London2nd Supervisor: Shaihan Malik, King’s College LondonClinical Champion: Vicky Goh, King’s College London Aim of the PhD Porject: Enabling high spatial resolution and big field of view imaging of the human body at 7T MRI. Developing a novel decoupling circuitry to combine a novel parallel transmit RF coil array AN INDIRECT LABELLING APPROACH TO TRACK THE THERAPEUTIC 1st supervisor: Ran Yan, King’s College London 2nd supervisor: John Maher, King’s College London Cell-based therapies have shown great promise in cancer treatment. One fundamental challenge in the successful development and clinical application of cellular therapeutics is the need to better understand the in vivo behaviour of adoptively infused cell products. This interdisciplinary project LATEST - EPSRC CDT IN SMART MEDICAL IMAGING CDT Career Talk Series: students gain exclusive insight from industry leaders and entrepreneurs. In the autumn of 2020, we hosted the first events of the CDT’s Career Talk Series, a new feature in our calendars in the 2020/21 academic year. The events provided an exclusive opportunity for attendees to engage with leaders in thebiomedical sector.
PEOPLE - EPSRC CDT IN SMART MEDICAL IMAGING Prof Gary Cook is Professor of PET Imaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London. He trained in radiology and then nuclear medicine in London. He is a clinical academic in the Cancer Imaging Department, BMEIS, KCL and an honorary consultant at Guy’s & St Thomas’ Hospitals.PARTNERSHIPS
Partnerships. Partnership with industry is essential to the success of the CDT. It enables translation of our research and strengthens our understanding of the commercial challenges in the medical imaging sector. There are many different ways for companies of all sizes and specialisms within the field to collaborate with the CDT. TELE-OPERATED ROBOTIC THROMBECTOMY IN ACUTE STROKE 1st supervisor: Thomas Booth, King’s College London2nd supervisor: Kawal Rhode, King’s College London3rd supervisor: Christos Bergeles, King’s College London Stroke is the second leading cause of death across the world, annually killing approximately 6 million people and the third leading cause of disability. In England, Wales and Northern Ireland, 85,000 people are hospitalised with CARDIAC MULTIPARAMETRIC MAGNETIC RESONANCE FINGERPRINTING 1st supervisor: Claudia Prieto, King’s College London 2nd supervisor: Daniel Rueckert, Imperial College London Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality in the Western world, causing over 65.000 deaths every year in England. Magnetic Resonance Imaging (MRI) is a very promising non-invasive tool for early risk assessment, guidance of therapy 3D CARDIAC MAGNETIC RESONANCE FINGERPRINTING WITH DEEP 3D cardiac magnetic resonance fingerprinting with deep learning. Magnetic Resonance Imaging (MRI) has become an important non-invasive tool for risk assessment and treatment monitoring of cardiovascular disease. Conventional MR images are qualitative measurements that depend on different parameters such as the longitudinal T1 and thetransverse
AI ENABLED MOTION CORRECTED QUANTITATIVE MRI OF THE FETAL 1st Supervisor: Jo Hajnal, King’s College London2nd Supervisor: Daniel Rueckert, Imperial College LondonClinical Champion: Mary Rutherford, King’s College LondonIndustry Supervisor: Johan van den Brink and Maarten Versluis Aim of the PhD Project: During the second half of pregnancy the human brain undergoes exuberant growth, with both microscopic and macropic changes happening rapidly. In MULTI-TRANSMIT TECHNOLOGY FOR OPTIMAL MAGNETIC RESONANCE 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Alexander Hammers, King’s College London There are increasing numbers of procedures in which electrodes are placed at depth in the human brain – both for recording and stimulation. While implanted electrode recordings are used in epilepsy treatment, DBS is HOW DO MEDICAL IMAGING RADIOISOTOPES USED FOR DIAGNOSTIC 1st supervisor: Samantha Terry, King’s College London 2nd supervisor: Gilbert Fruhwirth, King’s College London Aim of the PhD Project: Molecular imaging with radionuclides can pinpoint disease locations and measure changes in metabolism and gene expression. Also, reporter gene imaging has long been used to monitor cellular processes but has only recently been used with radionuclides ONE-STEP, SITE-SPECIFIC LABELLING OF HIS-TAGGED PROTEINS 1st Supervisor: Phil Blower, King’s College London2nd Supervisor: Michelle Ma, King’s College London Clinical Champion: Gary Cook, King’s College LondonIndustry Supervisor: Levente Meszaros Aim of the PhD Project:The project will combine new transition metal chemistry with protein engineering to produce and evaluate preclinically (in vitro, in vivo) a theranostic pair of HOME - EPSRC CDT IN SMART MEDICAL IMAGING Having reopened our recruitment for the 2021/22 academic year, we are pleased to announce that we are holding a virtual application clinic between 4pm-5pm GMT on 30 March, where CDT staff and students will be on hand to answer prospective applicants’ questions about the application process, including those concerning filling out theapplication form.
PHD PROGRAMMES
Whether it is through attendance as a delegate, speaking or organisation committee membership, involvement in conferences is an integral part of our students’ experience. APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGINGATLANTIC MEDICAL IMAGINGSIMON MEDICAL IMAGINGMEDICAL IMAGING ASSOCIATESMEDICAL IMAGING FLMEDICAL IMAGING JOBS Who should apply? Medical Imaging is a broad and diverse research area with students from a diverse range of backgrounds. Applicants will normally be expected to have first class, high upper second or Distinction degrees in any of the following subjects: THE CARDIAC DIGITAL TWIN 1st Supervisor: Steven Niederer, King’s College London 2nd Supervisor: Alistair Young, King’s College London Clinical Champion: Aldo Rinaldi, King’s College London Aim of the PhD Project: Imaging cardiac function, form and physiology through time Automatically quantify shape and function with uncertainty form cardiac images. Implement a Bayesian update for images to integratePARTNERSHIPS
Radhouene Neji, Senior Key Expert and Collaboration Manager for Magnetic Resonance at Siemens Healthineers: Siemens is involved with the EPSRC CDT in Smart Medical Imaging in various different ways, including sponsorship of several studentships, technology provision for research and, as one of Siemens’ imaging collaboration scientists based here at King’s, I myself am heavily involved with A DAY IN THE LIFE OF A PHD STUDENT It wouldn’t be an ordinary day without taking part in a Zoom call and almost instinctively asking the question “Can you hear me?”. As is such, I tuned in (or zoomed in?) for a group meeting at around 7:30 pm with Somali Academics to discuss our plans for the rest of the year. The lockdown has affected many students and in particular students from ethnic minority backgrounds, so we INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with FUNCTIONAL IMAGING OF LIVER USING CONTRAST-ENHANCED 1st Supervisor: Mengxing Tang, Imperial College London2nd Supervisor: Kirsten Christensen Jeffries, King’s College LondonIndustry Supervisor: Ying Luan Project Description / Background: This is an industrial PhD project aimed at developing novel imaging techniques for contrast-enhanced liver imaging using the ultrasound contrast agent (UCA) SonazoidTM. UCAs are micrometer size bubbles (with LEARNING THE SIGNATURE OF DISEASE IN ECHOCARDIOGRAPHY 1st supervisor: Pablo Lamata, King’s College London 2nd supervisor: Andy King, King’s College London The objective is the development and validation of methodology that automatically extracts diagnostic and prognostic biomarkers from echocardiographic sequences. The strategy will be to explicitly formulate the problem as a combination of sources of useful and confounding information. The FETAL QUANTITATIVE FLOW MEASUREMENT BY MRI 1st supervisor: Shaihan Malik, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Daniel Rueckert, Imperial College London The aim of this project is to develop and validate q-flow methods for assessing the fetal cardiovascular system and cerebral circulation using an image domain approach with full motion correction based on kt-sampling, novel HOME - EPSRC CDT IN SMART MEDICAL IMAGING Having reopened our recruitment for the 2021/22 academic year, we are pleased to announce that we are holding a virtual application clinic between 4pm-5pm GMT on 30 March, where CDT staff and students will be on hand to answer prospective applicants’ questions about the application process, including those concerning filling out theapplication form.
PHD PROGRAMMES
Whether it is through attendance as a delegate, speaking or organisation committee membership, involvement in conferences is an integral part of our students’ experience. APPLY NOW - EPSRC CDT IN SMART MEDICAL IMAGINGATLANTIC MEDICAL IMAGINGSIMON MEDICAL IMAGINGMEDICAL IMAGING ASSOCIATESMEDICAL IMAGING FLMEDICAL IMAGING JOBS Who should apply? Medical Imaging is a broad and diverse research area with students from a diverse range of backgrounds. Applicants will normally be expected to have first class, high upper second or Distinction degrees in any of the following subjects: THE CARDIAC DIGITAL TWIN 1st Supervisor: Steven Niederer, King’s College London 2nd Supervisor: Alistair Young, King’s College London Clinical Champion: Aldo Rinaldi, King’s College London Aim of the PhD Project: Imaging cardiac function, form and physiology through time Automatically quantify shape and function with uncertainty form cardiac images. Implement a Bayesian update for images to integratePARTNERSHIPS
Radhouene Neji, Senior Key Expert and Collaboration Manager for Magnetic Resonance at Siemens Healthineers: Siemens is involved with the EPSRC CDT in Smart Medical Imaging in various different ways, including sponsorship of several studentships, technology provision for research and, as one of Siemens’ imaging collaboration scientists based here at King’s, I myself am heavily involved with A DAY IN THE LIFE OF A PHD STUDENT It wouldn’t be an ordinary day without taking part in a Zoom call and almost instinctively asking the question “Can you hear me?”. As is such, I tuned in (or zoomed in?) for a group meeting at around 7:30 pm with Somali Academics to discuss our plans for the rest of the year. The lockdown has affected many students and in particular students from ethnic minority backgrounds, so we INVESTIGATING BRAIN DEVELOPMENT IN NEONATES USING 1st Supervisor: Enrico De Vita, King’s College London 2nd Supervisor: Jo Hajnal, King’s College London Aim of the PhD Project: Ultrahigh field (UHF) MRI (>=7T) offers increased sensitivity and research has shown significant potential improvements in data quality for a number of applications in adults. However few studies scanned children at 7T so far, with FUNCTIONAL IMAGING OF LIVER USING CONTRAST-ENHANCED 1st Supervisor: Mengxing Tang, Imperial College London2nd Supervisor: Kirsten Christensen Jeffries, King’s College LondonIndustry Supervisor: Ying Luan Project Description / Background: This is an industrial PhD project aimed at developing novel imaging techniques for contrast-enhanced liver imaging using the ultrasound contrast agent (UCA) SonazoidTM. UCAs are micrometer size bubbles (with LEARNING THE SIGNATURE OF DISEASE IN ECHOCARDIOGRAPHY 1st supervisor: Pablo Lamata, King’s College London 2nd supervisor: Andy King, King’s College London The objective is the development and validation of methodology that automatically extracts diagnostic and prognostic biomarkers from echocardiographic sequences. The strategy will be to explicitly formulate the problem as a combination of sources of useful and confounding information. The FETAL QUANTITATIVE FLOW MEASUREMENT BY MRI 1st supervisor: Shaihan Malik, King’s College London 2nd supervisor: Jo Hajnal, King’s College London 3rd supervisor: Daniel Rueckert, Imperial College London The aim of this project is to develop and validate q-flow methods for assessing the fetal cardiovascular system and cerebral circulation using an image domain approach with full motion correction based on kt-sampling, novel PEOPLE - EPSRC CDT IN SMART MEDICAL IMAGING Alan Spivey is Professor of Synthetic Chemistry in the Department of Chemistry at Imperial College London. His research encompasses the development of new catalysts for asymmetric group transfer reactions (acylation, sulfonyation & phosphorylation), germanium chemistry, chemical aspects of signal transduction, total synthesis and medicinal/imaging chemistry relating to asthma and cancer targets. EXPLORING THE INNER WORLD THROUGH A VIRTUAL WORLD 1st supervisor: Tomoki Arichi, King’s College London2nd supervisor: Jo Hajnal, King’s College LondonAdditional supervisor: Bernhard Kainz, Imperial College London Aim of the PhD Project: Develop a fully integrated immersive Virtual Reality (VR) experience in the MRI scanner. Integrate multi-modal sensory and physiological information into the VR experience to establish a new level of VR FUNCTIONAL IMAGING OF LIVER USING CONTRAST-ENHANCED 1st Supervisor: Mengxing Tang, Imperial College London2nd Supervisor: Kirsten Christensen Jeffries, King’s College LondonIndustry Supervisor: Ying Luan Project Description / Background: This is an industrial PhD project aimed at developing novel imaging techniques for contrast-enhanced liver imaging using the ultrasound contrast agent (UCA) SonazoidTM. UCAs are micrometer size bubbles (with HIGH RESOLUTION OPTIMAL PRECISION QUANTITATIVE MRI AT Figure 1: T1 mapping provides a quantitative measure of brain tissue properties that can be used for studying the brain health and disease. 7T MRI could be used to achieve much higher spatial resolution but the radiofrequency magnetic field varies strongly in the brain at this field strength. The result is highly variable precision in T1 estimation. This project seeks to create high precision LEARNING THE SIGNATURE OF DISEASE IN ECHOCARDIOGRAPHY 1st supervisor: Pablo Lamata, King’s College London 2nd supervisor: Andy King, King’s College London The objective is the development and validation of methodology that automatically extracts diagnostic and prognostic biomarkers from echocardiographic sequences. The strategy will be to explicitly formulate the problem as a combination of sources of useful and confounding information. The GENERAL PURPOSE ABNORMALITY DETECTION IN WHOLE BODY PET 1st Supervisor: Jorge Cardoso, King’s College London2nd Supervisor: Seb Ourselin, King’s College London Clinical Champion: Vicky Goh, King’s College LondonIndustry Supervisor: Elisabetta Grecchi Aim of the PhD Project: Develop AI methods that can predict healthy PET radiotracer uptake from anatomical data. Model the uncertainty of such predictions in a heteroscedastic (spatially varying DEEP-LEARNING PET-MR LONGITUDINAL RECONSTRUCTION FOR LOWER 1st Supervisor: Andrew Reader, King’s College London2nd Supervisor: Andy King, King’s College LondonClinical Champions: Vicky Goh and Gary Cook, King’s College London Aim of the PhD Project: This project explores new synergistic multi-modality data with an emphasis on AI-enhanced PET-MR image reconstruction methods, exploiting AI to improve imaging capabilities for cancer treatment INVESTIGATING THE EPILEPTIC BRAIN WITH SIMULTANEOUS EEG 1st supervisor: Ozlem Ipek, King’s College London 2nd supervisor: David Carmichael, King’s College London Clinical Champion: Alexander Hammers, King’s College London Aim of the PhD Project: Designing novel solutions into EEG design and MR hardware to improve simultaneous EEG/fMRI data. Develop an AI based algorithm to perform high-quality motion-free data collection with the advantage of PREDICTING AUTISM SPECTRUM PHENOTYPES FROM NEONATAL BRAIN 1st Supervisor: Dafnis Batalle, King’s College London2nd Supervisor: Maria Deprez, King’s College LondonClinical Champion: Grainne McAlonan, King’s College London Aim of the PhD Project: The goal of this project is to improve our understanding of brain development and outcome in babies at risk of autism spectrum disorders (ASD) by: Training machine learning algorithms in adult DEVELOPMENT OF A DECISION SUPPORT TOOL FOR NEUROIMAGING 1st supervisor: Daniel Rueckert, Imperial College London 2nd supervisor: Alexander Hammers, King’s College London The aims of this project are three-fold: Develop a machine learning (ML) classifier based on deep learning approaches, e.g. convolutional neural networks (CNNs), that can: detect early patterns of neurodegeneration; and differentiate between different patterns of* PhD Programme
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CROSS-INSTITUTIONAL COLLABORATION King’s College London and Imperial College London have complementary strengths in basic physical sciences, engineering and clinical translation. Our CDT brings together these two leading research- and educational-focused universities in close partnership.LATEST NEWS
RECRUITMENT RE-OPENS FOR OUR CDT IN SMART MEDICAL IMAGING The EPSRC Centre for Doctoral Training (CDT) in Smart Medical Imaging at King’s College London and Imperial College London continues the successful partnership of two world-class institutions, to provide PhD training within an embedded hospital environment in Central...read more
DIGITAL STORYTELLING MASTERCLASS In December 2019, a group of students from the CDT visited Facebook HQ for a hands on workshop run by the Ideas foundation and the Royal Academy of Engineers. The workshop aimed to equip attendees with the tools to change the face and image of biomedical engineering...read more
STUDENT EXPERIENCE: ICVSS SUMMER SCHOOL 2019 Margarita Bintsi shares her experience of meeting new people and enjoying recreational activities at ICSVSS Summer School; a week focusing on computer vision - the science and technology of making machines that see. Having in mind that summer schools can beextremely...
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STUDENT EXPERIENCE: CONFERENCES Jessica Hopson, who is currently in the first year of her PhD at the CDT in Smart Medical Imaging, writes about her experience at conferences early this year. After starting my PhD at the beginning of October, it wasn’t long before I attended my first conferences:the...
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RECRUITMENT OPENS FOR OUR CDT IN SMART MEDICAL IMAGING The EPSRC Centre for Doctoral Training (CDT) in Smart Medical Imaging at King’s College London and Imperial College London continues the successful partnership of two world-class institutions, to provide PhD training within an embedded hospital environment in Central...read more
A WORKSHOP EXPLORING PUBLIC ENGAGEMENT AT BIOMEDENG In early September the annual BioMedEng19 conference took place at Imperial College London. Branded as the largest gathering of Bioengineers, Biomedical and Medical Engineers in the UK, the conference offered the opportunity to catch up on the latest trendsand...
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THE AI WILL SEE YOU NOW: A PANEL DISCUSSION Jonny Jackson is a CDT PhD student with a research interest in how machine learning can be used to interpret medical images. In August he hosted a panel discussion to engage the general public with the debate around the future of Artificial Intelligence in...read more
CDT INDUSTRY-SUPERVISOR NETWORKING EVENT 2019 On Thursday 27 June, the CDT hosted a range of industry associates for its annual Supervisor-Industry Networking Event at St Thomas’ Hospital. The day provided the opportunity for the 29 industry associates attending to meet with supervisors, with some of ourstudents...
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Our students enter their programme as a cohort and maintain contact with each other throughout their research projects. They come from a variety of academic backgrounds, including engineering, chemistry, biology, mathematics, computer science, biochemistry and physics.Programme Structure
WORLD-LEADING RESEARCH Through our research, we look to build smart new technologies into the entire medical imaging process. PhD projects are directed towards at least one our smart medical imaging themes: AI-enabled imaging, Smart imaging probes, Emerging imaging and Affordable imaging.Available Projects
INDUSTRY PARTNERSHIP Our CDT was designed and is managed with the help of our industry partners. There are many ways for companies to engage with us, including research project sponsorship, Industrial Board membership, student placement opportunities, mentoring provision and more. Our Industry PartnersABOUT US
STUDENTS PER COHORT FROM A RANGE OF STEM BACKGROUNDS ACADEMIC SUPERVISORS FROM 19 DEPARTMENTS CLINICAL CHAMPIONS SUPERVISING STUDENTS HOSPITALS (NHS FOUNDATION TRUSTS) INVOLVED1M+
INDUSTRY FUNDING COMMITTED RESEARCH OPPORTUNITIES AI-ENABLED IMAGING E SMART IMAGING PROBES EEMERGING IMAGING E
AFFORDABLE IMAGING E LEARN MORE ABOUT OUR WORKApply Now
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