EPSRC Centre for Doctoral Training in Smart Medical Imaging at King's College London and Imperial College London
Lead Research Organisation:
King's College London
Department Name: Imaging & Biomedical Engineering
Abstract
Medical imaging has made major contributions to healthcare, by providing noninvasive diagnostics, guidance, and unparalleled monitoring of treatment and understanding of disease. A suite of multimodal imaging modalities is nowadays available, and scanner hardware technology continues to advance, with high-field, hybrid, real-time and hand-held imaging further pushing on technological boundaries; furthermore, new developments of contrast agents and radioactive tracers open exciting new avenues in designing more targeted molecular imaging probes. Conventionally, the individual imaging components of probes and contrast mechanisms, acquisition and reconstruction, and analysis and interpretation are addressed separately. This however, is creating unnecessary silos between otherwise highly synergistic disciplines, which our current EPSRC CDT in Medical Imaging at King's College London and Imperial College London has already started to successfully challenge. Our new CDT will push this even further by bridging the different imaging disciplines and clinical applications, with the interdisciplinary research based on complementary collaborations and new research directions that would not have been possible five years ago.
Through a comprehensive, integrated training programme in Smart Medical Imaging we will train the next generation of medical imaging researchers that is needed to reach the full potential of medical imaging through so-called "smart" imaging technologies. To achieve this ambitious goal we have developed four new Scientific Themes which are synergistically interlinked: AI-enabled Imaging, Smart Imaging Probes, Emerging Imaging and Affordable Imaging. This is complemented by a dedicated 1+3 training programme, with a new MRes in Healthcare Technologies at King's as the foundation year, strong industry links in form of industry placements, careers mentoring and workshops, entrepreneurship training, and opportunities in engaging with international training programmes and academic labs to become part of a wider cohort. Cohort building, Responsible Research & Innovation, Equality, Diversity & Inclusion, and Public Engagement will be firmly embedded in this programme. Students graduating from this CDT will have acquired a broad set of scientific and transferable skills that will enable them to work across the different medical imaging sub-disciplines, gaining a high employability over wider sectors.
Through a comprehensive, integrated training programme in Smart Medical Imaging we will train the next generation of medical imaging researchers that is needed to reach the full potential of medical imaging through so-called "smart" imaging technologies. To achieve this ambitious goal we have developed four new Scientific Themes which are synergistically interlinked: AI-enabled Imaging, Smart Imaging Probes, Emerging Imaging and Affordable Imaging. This is complemented by a dedicated 1+3 training programme, with a new MRes in Healthcare Technologies at King's as the foundation year, strong industry links in form of industry placements, careers mentoring and workshops, entrepreneurship training, and opportunities in engaging with international training programmes and academic labs to become part of a wider cohort. Cohort building, Responsible Research & Innovation, Equality, Diversity & Inclusion, and Public Engagement will be firmly embedded in this programme. Students graduating from this CDT will have acquired a broad set of scientific and transferable skills that will enable them to work across the different medical imaging sub-disciplines, gaining a high employability over wider sectors.
Planned Impact
Strains on the healthcare system in the UK create an acute need for finding more effective, efficient, safe, and accurate non-invasive imaging solutions for clinical decision-making, both in terms of diagnosis and prognosis, and to reduce unnecessary treatment procedures and associated costs. Medical imaging is currently undergoing a step-change facilitated through the advent of artificial intelligence (AI) techniques, in particular deep learning and statistical machine learning, the development of targeted molecular imaging probes and novel "push-button" imaging techniques. There is also the availability of low-cost imaging solutions, creating unique opportunities to improve sensitivity and specificity of treatment options leading to better patient outcome, improved clinical workflow and healthcare economics. However, a skills gap exists between these disciplines which this CDT is aiming to fill.
Consistent with our vision for the CDT in Smart Medical Imaging to train the next generation of medical imaging scientists, we will engage with the key beneficiaries of the CDT: (1) PhD students & their supervisors; (2) patient groups & their carers; (3) clinicians & healthcare providers; (4) healthcare industries; and (5) the general public. We have identified the following areas of impact resulting from the operation of the CDT.
- Academic Impact: The proposed multidisciplinary training and skills development are designed to lead to an appreciation of clinical translation of technology and generating pathways to impact in the healthcare system. Impact will be measured in terms of our students' generation of knowledge, such as their research outputs, conference presentations, awards, software, patents, as well as successful career destinations to a wide range of sectors; as well as newly stimulated academic collaborations, and the positive effect these will have on their supervisors, their career progression and added value to their research group, and the universities as a whole in attracting new academic talent at all career levels.
- Economic Impact: Our students will have high employability in a wide range of sectors thanks to their broad interdisciplinary training, transferable skills sets and exposure to industry, international labs, and the hospital environment. Healthcare providers (e.g. the NHS) will gain access to new technologies that are more precise and cost-efficient, reducing patient treatment and monitoring costs. Relevant healthcare industries (from major companies to SMEs) will benefit and ultimately profit from collaborative research with high emphasis on clinical translation and validation, and from a unique cohort of newly skilled and multidisciplinary researchers who value and understand the role of industry in developing and applying novel imaging technologies to the entire patient pathway.
- Societal Impact: Patients and their professional carers will be the ultimate beneficiaries of the new imaging technologies created by our students, and by the emerging cohort of graduated medical imaging scientists and engineers who will have a strong emphasis on patient healthcare. This will have significant societal impact in terms of health and quality of life. Clinicians will benefit from new technologies aimed at enabling more robust, accurate, and precise diagnoses, treatment and follow-up monitoring. The general public will benefit from learning about new, cutting-edge medical imaging technology, and new talent will be drawn into STEM(M) professions as a consequence, further filling the current skills gap between healthcare provision and engineering.
We have developed detailed pathways to impact activities, coordinated by a dedicated Impact & Engagement Manager, that include impact training provision, translational activities with clinicians and patient groups, industry cooperation and entrepreneurship training, international collaboration and networks, and engagement with the General Public.
Consistent with our vision for the CDT in Smart Medical Imaging to train the next generation of medical imaging scientists, we will engage with the key beneficiaries of the CDT: (1) PhD students & their supervisors; (2) patient groups & their carers; (3) clinicians & healthcare providers; (4) healthcare industries; and (5) the general public. We have identified the following areas of impact resulting from the operation of the CDT.
- Academic Impact: The proposed multidisciplinary training and skills development are designed to lead to an appreciation of clinical translation of technology and generating pathways to impact in the healthcare system. Impact will be measured in terms of our students' generation of knowledge, such as their research outputs, conference presentations, awards, software, patents, as well as successful career destinations to a wide range of sectors; as well as newly stimulated academic collaborations, and the positive effect these will have on their supervisors, their career progression and added value to their research group, and the universities as a whole in attracting new academic talent at all career levels.
- Economic Impact: Our students will have high employability in a wide range of sectors thanks to their broad interdisciplinary training, transferable skills sets and exposure to industry, international labs, and the hospital environment. Healthcare providers (e.g. the NHS) will gain access to new technologies that are more precise and cost-efficient, reducing patient treatment and monitoring costs. Relevant healthcare industries (from major companies to SMEs) will benefit and ultimately profit from collaborative research with high emphasis on clinical translation and validation, and from a unique cohort of newly skilled and multidisciplinary researchers who value and understand the role of industry in developing and applying novel imaging technologies to the entire patient pathway.
- Societal Impact: Patients and their professional carers will be the ultimate beneficiaries of the new imaging technologies created by our students, and by the emerging cohort of graduated medical imaging scientists and engineers who will have a strong emphasis on patient healthcare. This will have significant societal impact in terms of health and quality of life. Clinicians will benefit from new technologies aimed at enabling more robust, accurate, and precise diagnoses, treatment and follow-up monitoring. The general public will benefit from learning about new, cutting-edge medical imaging technology, and new talent will be drawn into STEM(M) professions as a consequence, further filling the current skills gap between healthcare provision and engineering.
We have developed detailed pathways to impact activities, coordinated by a dedicated Impact & Engagement Manager, that include impact training provision, translational activities with clinicians and patient groups, industry cooperation and entrepreneurship training, international collaboration and networks, and engagement with the General Public.
Organisations
- King's College London (Lead Research Organisation)
- University of Lausanne (UNIL) (Project Partner)
- Medicines Discovery Catapult (Project Partner)
- Lightpoint Medical Ltd (Project Partner)
- Ultromics Ltd (Project Partner)
- Xtronics Ltd. (Project Partner)
- Graduiertenkolleg BIOQIC (Project Partner)
- Memorial Sloan- Kettering Cancer Centre (Project Partner)
- Massachusetts General Hospital East (Project Partner)
- HeartFlow Inc. (Project Partner)
- Mirada Medical UK (Project Partner)
- Optellum Ltd (Project Partner)
- NIHR Imperial Biomedical Research Centre (Project Partner)
- The University of Hong Kong (Project Partner)
- German Cancer Research Center (Project Partner)
- Stanford University (Project Partner)
- Massachusetts Institute of Technology (Project Partner)
- Theragnostics Ltd (Project Partner)
- QUIBIM (Project Partner)
- NVIDIA Limited (UK) (Project Partner)
- University of Copenhagen (Project Partner)
- King's College Hospital NHS Foundn Trust (Project Partner)
- Brainminer (Project Partner)
- Biotronics 3D Ltd (Project Partner)
- GSK (Project Partner)
- Nagoya University (Project Partner)
- South London and Maudsley NHS Trust (Project Partner)
- Perspectum Diagnostics (Project Partner)
- Brigham and Women's Hospital (Project Partner)
- Vienna General Hospital (Project Partner)
- Radiologics Inc (Project Partner)
- Imanova Limited (Project Partner)
- GSTT NIHR Biomedical Research Centre (Project Partner)
- icometrix (Project Partner)
- PHILIPS MEDICAL SYSTEMS NEDERLAND BV (Project Partner)
- Image Analysis Group (Project Partner)
- MR Code BV (Project Partner)
- ASTRAZENECA UK LIMITED (Project Partner)
- Therapanacea (Project Partner)
- Siemens Healthineers (Project Partner)
- GE Healthcare (Project Partner)
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/S022104/1 | 30/09/2019 | 30/03/2028 | |||
2271377 | Studentship | EP/S022104/1 | 30/09/2019 | 30/03/2024 | Shane Angoh |
2269804 | Studentship | EP/S022104/1 | 30/09/2019 | 30/12/2024 | Ioannis Valasakis |
2271380 | Studentship | EP/S022104/1 | 30/09/2019 | 29/06/2024 | Suryava Bhattacharya |
2271386 | Studentship | EP/S022104/1 | 30/09/2019 | 14/10/2024 | Virginia Fernandez |
2269728 | Studentship | EP/S022104/1 | 30/09/2019 | 30/12/2023 | Gregor Ekart |
2271390 | Studentship | EP/S022104/1 | 30/09/2019 | 29/05/2024 | Yannick Brackenier |
2269879 | Studentship | EP/S022104/1 | 30/09/2019 | 29/09/2023 | Lydia Smith |
2269756 | Studentship | EP/S022104/1 | 30/09/2019 | 30/03/2023 | Guillaume Corda |
2271372 | Studentship | EP/S022104/1 | 30/09/2019 | 29/06/2024 | Marica Muffoletto |
2271375 | Studentship | EP/S022104/1 | 30/09/2019 | 29/09/2023 | Robert Holland |
2269678 | Studentship | EP/S022104/1 | 30/09/2019 | 29/09/2023 | Aidan Michaels |
2269873 | Studentship | EP/S022104/1 | 30/09/2019 | 29/04/2024 | Lindsay Munroe |
2269818 | Studentship | EP/S022104/1 | 30/09/2019 | 29/06/2024 | Jyoti Mangal |
2322101 | Studentship | EP/S022104/1 | 06/01/2020 | 04/09/2024 | Mariana Ferreira Teixeira Da Silva |
2435042 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Donovan Tripp |
2442179 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Theodore Barfoot |
2442176 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Rifkat Zaydullin |
2442177 | Studentship | EP/S022104/1 | 30/09/2020 | 24/10/2021 | Robin Andlauer |
2440765 | Studentship | EP/S022104/1 | 30/09/2020 | 29/09/2025 | Natasha Patel |
2442175 | Studentship | EP/S022104/1 | 30/09/2020 | 29/05/2025 | Paula Ramirez Gilliland |
2438829 | Studentship | EP/S022104/1 | 30/09/2020 | 30/03/2025 | Jie Tang |
2424334 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Barbara Dworakowska |
2424288 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Ashay Patel |
2442183 | Studentship | EP/S022104/1 | 30/09/2020 | 30/03/2025 | William Lim Kee Chang |
2435447 | Studentship | EP/S022104/1 | 30/09/2020 | 30/03/2025 | Hugo Barbaroux |
2434728 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Denis Prokopenko |
2435136 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Felix Horger |
2442178 | Studentship | EP/S022104/1 | 30/09/2020 | 30/12/2024 | Simon Dahan |
2440754 | Studentship | EP/S022104/1 | 30/09/2020 | 29/03/2022 | Maxwell Buckmire-Monro |
2440156 | Studentship | EP/S022104/1 | 30/09/2020 | 29/06/2025 | Joana Machado |
2434687 | Studentship | EP/S022104/1 | 02/10/2020 | 29/09/2024 | Benjamin Woolley |
2605296 | Studentship | EP/S022104/1 | 30/09/2021 | 31/10/2025 | Ke Wen |
2606581 | Studentship | EP/S022104/1 | 30/09/2021 | 30/10/2025 | Abhijit Adhikary |
2604976 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Chris Taylor |
2605660 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Nathan Wong |
2606493 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Fatma Alimahomed |
2606532 | Studentship | EP/S022104/1 | 30/09/2021 | 30/11/2025 | Diego Fajardo Rojas |
2606566 | Studentship | EP/S022104/1 | 30/09/2021 | 30/11/2025 | Olga Tyurina |
2604983 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2026 | Jack Oldroyd |
2605674 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Tia Gibson |
2606550 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Meng Wei |
2605686 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Yaqing Luo |
2605289 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Jacob Wilson |
2606444 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Clotilde Vie |
2605292 | Studentship | EP/S022104/1 | 30/09/2021 | 29/09/2025 | Kate Cevora |
2739943 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Aline Buat |
2740519 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | George Obada |
2741220 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Maha Alshammari |
2740873 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Oluwatosin Alabi |
2740858 | Studentship | EP/S022104/1 | 30/09/2022 | 30/11/2026 | Aisleen Whelan |
2740489 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Rory Kenrick |
2740000 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Iman Islam |
2739967 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Aryan Esfandiari |
2740751 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Teodora Catargiu |
2740931 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Helena Sousa |
2740407 | Studentship | EP/S022104/1 | 30/09/2022 | 31/05/2027 | Paul Gape |
2741285 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Poppy Tobolski |
2741200 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Aakash Saboo |
2740733 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Manisha Sahota |
2741301 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Yiyang Xu |
2740586 | Studentship | EP/S022104/1 | 30/09/2022 | 29/09/2026 | Dewmini Wickremasinghe |
2886591 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Riccardo Cavarra |
2886561 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Movindu Dassanayake |
2886553 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Lorena Garcia-Foncillas Macias |
2886403 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | George Webber |
2880683 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Cliona Ni Chochlain |
2886603 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Shambhavi Malik |
2886605 | Studentship | EP/S022104/1 | 30/09/2023 | 30/12/2027 | Victoria Stomberg |
2885098 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Christina Siakalli |
2883714 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Anthea Macintosh-Larocque |
2886504 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Lito Chatzidavari |
2886608 | Studentship | EP/S022104/1 | 30/09/2023 | 29/09/2027 | Yuang You |
2904538 | Studentship | EP/S022104/1 | 01/02/2024 | 31/01/2028 | Paloma Nashira Rodriguez Baena |
2904562 | Studentship | EP/S022104/1 | 01/02/2024 | 31/01/2028 | Charel Mangama Sindzi |
2904561 | Studentship | EP/S022104/1 | 01/02/2024 | 31/01/2028 | Adriana Namour |
2904564 | Studentship | EP/S022104/1 | 01/02/2024 | 31/01/2028 | Rene Kornmann |
2928974 | Studentship | EP/S022104/1 | 06/10/2024 | 30/03/2028 | Victoria Stomberg |