Prof Seb Ourselin
Prof Seb Ourselin is Head of the School of Biomedical Engineering & Imaging Sciences at King’s College London, which is dedicated to the development, clinical translation and clinical application of medical imaging, computational modelling, minimally invasive interventions and surgery. He is Director of the Wellcome / EPSRC Centre for Interventional and Surgical Sciences and the EPSRC Image-Guided Therapies UK Network+ and has raised over £40M as Principal Investigator, including £10M under the Innovative Engineering for Health initiative to create the GIFT-Surg project.
He is co-founder of Brainminer, an academic spin-out commercialising machine learning algorithms for brain image analysis. Their first product, DIADEM, a clinical decision support system for dementia diagnosis, is CE marked and medically approved.
He has published over 400 articles and is an associate editor for IEEE Transactions on Medical Imaging, Journal of Medical Imaging, Nature Scientific Reports, and Medical Image Analysis. He has been active in conference organisation (12 international conferences as General or Program Chair) and professional societies (APRS, MICCAI). He was elected Fellow of the MICCAI Society in 2016.
Dr Christos Bergeles
Dr Christos Bergeles is the CDT Deputy Director and a senior lecturer in in the in the Surgical & Interventional Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London.
He received a PhD in Robotics from ETH Zurich, Switzerland, in 2011. He was a postdoctoral research fellow at Boston Children’s Hospital, Harvard Medical School, Massachusetts, and the Hamlyn Centre for Robotic Surgery, Imperial College, United Kingdom. He became a Lecturer (Assistant Professor) at UCL in September 2015, where he was a core-founding member of the the Wellcome EPSRC Centre for Interventional and Surgical Sciences. He joined King’s College London in July 2018 as a Senior Lecturer (Associate Professor). Dr.Bergeles received the Fight for Sight Award in 2014, an ERC Starting Grant in 2016, and an NIHR Invention for Innovation Grant in 2017. He is leading the Robotics and Vision in Medicine Lab (RViM), whose mission is to develop image-guided micro-surgical robots that assist the delivery of regenerative therapies deep inside the human body.
Responsible for managing all aspects of administration in the CDT, including adherence to King's regulations, student recruitment and managing all processes involved with the student lifecycle. The first point of contact for all parties involved in the CDT, working closely with the CDT Management Team as well as other central College services including the Centre for Doctoral Studies, Registry Services and the Admissions Centre.
Dr Jordi Alastruey
Dr Jordi Alastruey is based in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His group (www.haemod.uk) studies blood flow in the cardiovascular system using clinical data and modelling (computational and experimental). They study methods for cardiovascular function assessment based on the analysis of pulse wave signals. These are produced by cardiac contraction, which generates a pulse wave that is transmitted through the arteries, leading to a rhythmical expansion and contraction of arteries (e.g. producing the pulse felt in the wrist). Pulse wave signals can be measured in vivo using a variety of devices and are influenced by the heart and the vasculature, making them a rich source of information on cardiovascular health.
Current projects in collaboration with medical doctors, imaging scientists and mathematicians include the development of algorithms for (i) reconstructing the central (aortic) blood pressure wave from the aortic flow wave acquired by MRI and (ii) investigating cardiovascular determinants of hypertension such as arterial stiffness and ventricular ejection.
Dr Oleg Aslanidi
Dr Oleg Aslanidi is a Reader in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His main research interests are in computational modelling of the heart and cardiac arrhythmias, as well as imaging modalities that enable the reconstruction of the 3D heart structure in health and disease. Despite a vast amount of clinical data from patients and cell to organ level experiments, complex arrhythmogenic mechanisms in the entire heart remain unclear. Computational modelling provides a quantitative framework for integrating multimodal imaging and experimental data in-silico. Validated computational tools can be applied for dissecting patient-specific arrhythmia mechanisms and predicting optimal treatments, and therefore can assist in clinical decision-making.
Dr Mads Bergholt
Mads is a lecturer in biophotonics in the Craniofacial Development and Stem Cell Biology division of the Faculty of Dentistry, Oral & Craniofacial Sciences at King’s College London. He received his MSc. Degree in Engineering, Physics and Technology (optics) from the University of Southern Denmark and his Ph.D. in Biomedical Engineering (Bioimaging) from National University of Singapore. He was awarded the Marie Curie Fellowship at Imperial College London and the United Kingdom Regenerative Medicine Platform (UKRMP) Special Merit Prize. He is currently a Lecturer in Biophotonics at Kings College London. He has published over 28 original research papers. His research interests include biomedical optics and light-tissue interaction, linear/non-linear optical spectroscopy/imaging, advanced endoscopy and artifical intelligence. He holds several commercialized patents in healthcare.
Dr Martin Bishop
Dr Martin Bishop is a Reader in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research focuses on Computational Cardiac Electrophysiology. He uses high-resolution, multi-model imaging data, from both the clinic and the experimental lab, to construct very detailed computational models of the heart, further parameterised with functional experimental measurements. These models are then used within state-of-the-art cardiac simulation environments to conduct in-silico experiments probing hitherto unknown mechanisms of the functioning of the heart in both health and disease. Specifically, his research examines the mechanisms underlying how and why the normal, synchronised electrical activation of the heart may break-down into highly disorganised ‘arrhythmic’ behaviour, in order to develop better preventative and therapeutic measures.
Dr Thomas Booth
Thomas C Booth is a Senior Lecturer in the Department of Neuroimaging at King's College London and an Honorary Consultant Diagnostic and Interventional Neuroradiologist at King's College Hospital. His interests are in neuro-oncology imaging (including advanced MRI techniques and machine learning), neurovascular (aneurysm treatment; stroke imaging patient stratification); and incidental finding research (deep learning abnormality detection). Much of his focus is on brain tumour treatment response assessment using brain tumour MRI – he is reminded continuously how important neuro-oncology diagnostics are when presenting patients at the neuro-oncology multi-disciplinary team meetings in a busy London teaching hospital.
Thomas sits on the National Cancer Research Institute Brain Tumour Committee, the Royal College of Radiologists Academic Committee and the Royal College of Radiologists AI Policy Reference Group. He was recently awarded the inaugural Royal College of Radiologists Outstanding Researcher Award.
Dr David Carmichael
Dr David Carmichael is a reader in MRI in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. He has a background in MRI Physics, which over time has developed into a wider interest in developing and applying new combinations of imaging techniques to measure and understand the human brain across spatial and temporal scales.
David has a particular interest in the application of these methods in the study of epilepsy. Modern neuroimaging play a number of vital roles in this context. They can be used to non-invasively identify (map) epileptogenic brain regions. However, they can also go far beyond this and be used to measure the complex interactions between brain areas and how these relate to the unwanted synchronous brain activity found in epilespy. Crucially, both the mapping and characterisation of brain dynamics can inform and assess treatment approaches for example via surgery or electrical stimulation.
Dr Adelaide De Vecchi
Dr Adelaide de Vecchi is a Lecturer in Computational Cardiovascular Modelling in the Department of Biomedical Engineering within the School of Biomedical Engineering & Imaging Sciences at King’s College London. The focus of her research is on the field of personalised medicine, specifically on the clinical translation of computational modelling applied to cardiovascular diseases. She has developed personalised models of fluid-structure interaction based on state-of-the-art imaging data, including CT, Phase-Contrast MRI (4d flow) and 3D+t Colour Doppler data. These models have been used to gain insight into the pathophysiology of congenital heart diseases (e.g. single ventricle pathologies) and to evaluate medical devices (e.g. bioprosthetic mitral valves) in the individual patient. Her research has a strong emphasis on multi-disciplinarity and clinical translation, and she works in close collaboration with cardiologists, surgeons, imaging scientists and software developers.
Dr Isabel Dregely
Dr Isabel Dregely is a Lecturer in PET/MRI Acquisition & Reconstruction in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Her research interest is simultaneous PET/MR imaging. These hybrid systems have recently become available and promise a non-invasive comprehensive tissue characterization. However, the technology still faces the following limitations: 1) There is a mismatch between a complex multi-contrast MR vs. a simple “push-button” PET acquisition scan. 2) Patient motion during long scan acquisitions corrupts image quality. 3) There is no standardized procedure on how to combine the complex, multi-parametric information to generate clinically meaningful biomarkers of disease. To address these challenges, her research is focused on methods to integrate MRI and PET throughout acquisition, image reconstruction and post-processing. The clinical goals are to provide image-based quantitative information about the individual’s cancerous tissue biology to create opportunities to advance patient care.
Prof Jo Hajnal
Professor Jo Hajnal is Chair in Imaging Science at King’s College London. His research interests include in vivo imaging, particularly Magnetic Resonance Imaging (MRI), optical imaging and Ultrasound. A key theme has been integrating data acquistion with reconstruction and image analysis to acheive an integrated pipeline in which each element supports and is supported by the other key elements. Fetal imaging is a primary interest with major projects running to develop comprehensive fetal imaging methods incorporating new methods for both MRI and ultrasound.
Dr Özlem Ipek
Özlem Ipek is lecturer of ultra-high Field MRI engineering at the Department of Biomedical Engineering at King’s College London. After completing physics (METU, Turkey) and applied physics degree (TU/e, Netherlands), she received her PhD degree in 2014 from Utrecht University, Netherlands. She was a scientist and managing director of the RF lab at EPFL, Switzerland before moving to KCL. Her research interest is developing, designing and prototyping MRI hardware for 7 Tesla MRI scanner and clinical MRI scanners for body and neuro imaging. She supervised over 12 student projects, 3 master thesis and several PhD students including one as an official co-supervisor. She has over ten years of experience on 7 Tesla MRI parallel-transmit RF technology and MRI safety management.
Prof Prashant Jha
Prof Prashant Jha is an editor, inventor and serial entrepreneur who trained in medicine, bioengineering, product design, computer science, strategy and innovation management. He serves as the Professor of Health Innovations in the Faculty of Life Sciences and Medicine at King’s College London and heads the affordable medical technologies division at the School of Biomedical Engineering and Life Sciences. As a serial entrepreneur, he has set venture-backed businesses in the domains of vaccine delivery, personalized oncology, internet services, education technology and medical devices over the last fifteen years.
He has co-invented eight medical devices in the areas of stress urinary incontinence, haemorrhoid surgery, labour monitoring, stroke detection, pulmonary medicine and diabetes management. He has adjunct appointments at medical, engineering and business schools in Japan, Australia, India and Europe - with whom he works to create a global ecosystem for developing low-cost, high-impact medical devices. As a medical editor, he serves as the Senior Editor for The BMJ and is the co-founder and editor of BMJ Innovations, the world's first medical innovations journal focused on devices, diagnostics, and digital health.
Dr Pablo Lamata
Dr Pablo Lamata is a Wellcome Trust Senior Research Fellow and an Honorary Reader in Computational Cardiology at King’s College of London. His research interest focuses in the combination of imaging and computational modelling technologies to improve the management of cardiovascular diseases. He develops solutions to stratify subjects according to the remodelling of cardiac anatomy, to characterise the performance of the heart during diastole, and to assess non-invasively the pressure driving blood flow.
His team (http://cmib.website) has developed solutions for the identification of faulty valves, for the detection of growth differences caused by pre-term birth, or for the optimal patient selection for ablation or resynchronization therapies, among others. He coordinates the EU consortium "Personalised In-Silico Cardiology” (http://picnet.eu) that develops modelling methodologies to optimize clinical protocols, from data acquisition to device parameters and intervention choices.
Dr Jack Lee
Dr Jack Lee is Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. The major focus of his group is on characterising the pathophysiology of whole-heart cardiac perfusion and mechanics, and in order to address this, a combination of image & signal processing techniques, finite element analysis, and inverse parameterisation to patient-specific clinical data are employed. These models combined with advanced clinical imaging allow personalised modelling pipelines to diagnose disease, add refined interpretation to the medical data and predict outcomes of interventions. Read more about Jack’s research on his group’s website.
Dr Shaihan Malik
Dr Shaihan Malik is a Senior Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research focuses primarily on parallel transmission MRI – this is a next generation technology allowing flexible and dynamic control of radiofrequency (RF) magnetic fields. These fields are used in MRI to generate the signals that then form images. The properties of these fields depend on the interaction between the scanner and the patient, though until recently it has not been possible to influence them directly. New “parallel transmission” technology is changing this, opening possibilities for tailoring image acquisitions to individual subjects to achieve faster scanning, large reductions in inter-subject variability and even new types of imaging with complex RF pulses. He is focused on such technical developments and their translation into clinical benefits using a state-of-the-art prototype MRI system at St. Thomas’.
Prof Paul Marsden
Paul Marsden is Professor of PET Physics at King’s College London. He led the early development of combined PET and MRI multimodality imaging systems and his research interests include all aspects of PET imaging from detectors and imaging systems through to data acquisition and analysis methods for clinical and research PET studies. Much of this involves collaborating with clinicians and scientists in oncology, cardiology and neuropsychiatry. As Director of Medical Physics at Guy’s and St Thomas’ PET Centre Paul is familiar with the regulatory, logistical and technical issues associated with PET imaging. He is co-lead of the UK PET Core Lab and General Chair of the 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference.
Dr Marc Modat
Marc Modat is a Senior Lecturer in the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research interests cover amongst others the development of novel imaging biomarkers especially for neurodegenerative diseases. He has significant expertise in medical image registration as well as in medical image segmentation and machine learning. He is also promoting the translation of state-of-the-art engineering solutions to clinical research and clinical practices.
Prof Steven Niederer
Steven Niederer is Professor of Biomedical Engineering in the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research is characterised by the use of multi-scale and multi-physics computational models of the heart to investigate fundamental physiological questions and gain insight into patient pathologies and treatments. This work includes the development of novel methods for integrating and interpreting patient data, evaluating new medical devices using computational modelling and developing patient specific models. His research is highly interdisciplinary, working closely with imaging scientists, basic researchers and cardiologist with a strong focus on clinical translation.
Dr David Nordsletten
Dr David Nordsletten is a Reader in Cardiovascular Biomechanics at King’s College London. His principal emphasis in his research team is the integration of biomechanical modeling and advanced numerical techniques with clinical imaging. This merger of disparate – yet mutually complementary – fields provides a new paradigm for analyzing and assessing health and disease, moving toward personalized patient care. Through the development of patient-specific mathematical models, they construct novel analysis tools to improve diagnosis, treatment and therapy planning in the heart. A key area of emphasis in their lab is the biomechanics of both healthy and failing hearts. Using biomechanical analysis software, they aim to characterize alterations in cardiac structure and function in disease.
Prof Andrew Reader
Andrew Reader is Professor of Imaging Sciences in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His primary research interest concerns image reconstruction and modelling for positron emission tomography (PET), and more recently its integration with simultaneous magnetic resonance imaging (MRI). Particular topics include multi-parametric simultaneous PET-MR imaging, high resolution PET imaging of the brain, kinetic analysis, fully 4D image reconstruction and direct kinetic parameter estimation. He is passionate about learning of existing methodologies and then seeking to innovate, in order to demonstrate new possibilities without being prematurely concerned about the computational burden of novel approaches. Bayesian methods for estimation of end point parameters of interest directly from raw medical imaging data, along with improved modelling of the signal and noise components in the data, allow notable noise reduction and improved spatial resolution to be achieved in medical imaging.
Recent research output highlights include simultaneous water and glucose metabolism imaging with PET, creation of multi-subject radiotracer-specific brain atlases for use in automated analysis and as priors in image reconstruction, and direct kinetic parameter estimation for raclopride imaging of the dopaminergic system.
Prof Kawal Rhode
Kawal Rhode is Professor of Biomedical Engineering and Head of Education in the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research team develops novel technology-based solutions to healthcare problems, particularly heart disease. Solutions are developed by his multi-disciplinary team and in partnership with clinicians at St. Thomas’ hospital and a number of international industrial partners. Examples of current work include clinically-useful quantification of medical images, development of image-guided solutions for cardiac interventions, development of catheter and imaging robots, computer-based automation of analyses and interventions and development of tele-health solutions.
Dr Sebastien Roujol
Dr Sebastien Roujol is a Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His broad research interests is on the development of novel cardiac MRI methods and image processing algorithms to assess patient pathologies and monitor clinical treatments. One of his main focus is to develop new methods to plan and monitor ablation procedures of cardiac arrhythmias. This work includes novel developments for quantitative/qualitative myocardial tissue characterization for assessment of the cardiac arrhythmogenic substrate, multi-modal co-registration of MRI and electrophysiology data for procedure planning, real time MRI-guidance for ablation lesion assessment.
Dr Rachel Sparks
Rachel Sparks is a Lecturer in Surgical and Interventional Engineering at the School of Biomedical Engineering & Imaging Sciences, King’s College London. The primary focus of her research is on developing computer assisted planning and image-guided navigation techniques to increase accuracy of targeting pathologic structures and improve safety during surgical treatments. This work involves building patient-specific models of anatomy, and using these models to provide quantitative measures of risk and efficacy related to surgical interventions, including the placement of tools, removal or thermal treatment of tissue.
Ongoing work in her group is focused on using deep learning to improve the ability identify and delineate important structures of interest within the brain (e.g. vasculature, white matter tracts, and pathology) as well as to simulate tissue response to surgical interventions. These techniques are translated into the clinical as part of the Epilepsy-Navigator (EpiNavTM) software platform to provide clinical tools for the diagnosis and treatment of epilepsy.
Prof Tom Vercauteren
Tom is Professor of Interventional Image Computing within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research focuses on translational medical image computing and machine learning with a specific interest in their applications to surgery and interventional sciences. Prior to this, Tom was Associate Professor at University College London (UCL) where he acted as Deputy Director for the Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS). In his previous industrial tenure at Mauna Kea Technologies, he served as New Technologies Manager to identify emerging technologies and support their acquisition within the company and led the company image computing group. Tom received his PhD, co-supervised by Nicholas Ayache and Xavier Pennec at Inria Sophia Antipolis, in 2008 from Ecole des Mines de Paris. He obtained his Master of Science in Electrical Engineering at Columbia University in 2004 and graduated from Ecole Polytechnique in 2003.
Dr Wenfeng Xia
Dr Wenfeng Xia’s research is centred on the development and clinical translation of novel medical devices to improve patient outcomes during surgical and interventional procedures. One area of research focus is photoacoustic imaging, an emerging modality that provides rich optical contrast with highly scalable spatial resolution and penetration depth, proven to have great potential for many pre-clinical and clinical applications. A second area of focus is ultrasonic tracking to identify the tip of medical device during many ultrasound image-guided minimally invasive procedures.