CISTIB - Key Persons
Amy M. Barker is Project Manager at CISTIB, in the School of Computing, University of Leeds. She completed her PhD in 2018, working with Professor Peter G. Stockley in the Faculty of Biological Sciences, specialising in characterisation of RNA:protein interactions involved in the formation of virus-like particles. Amyà à às experience ranges from laboratory technician to running biophysical analytical services within the Centre for Biomolecular Interactions, Astbury Centre, University of Leeds. After a successful post as Research Fellow in Cellular and Molecular Virology with Professor Adrian Whitehouse (2019-2021), Amy joined the CISTIB team to provide professional support to the Diamond Jubilee Chair, Professor Alejandro F. Frangi.
After studying here at the University of Leeds, I graduated in May 2021 with a BEng in Mechanical Engineering. During my undergraduate degree, I undertook a year's industrial placement with BuroHappold Engineering. I split my time over the Building Services and the Sustainability & Physics teams. Over the course of my final year, I completed my dissertation project under the supervision of Dr Zieke Taylor. I investigated the use of physics-informed neural networks to predict the deformation of soft tissues. I will now be continuing my research within the field of physics-informed machine learning as I commence my PhD in Autumn 2021, supervised by Dr Zieke Taylor and Dr Nishant Ravikumar.
I studied my BSc in Mathematics at Universidad de Guadalajara, and then my MSc Degree in Advanced Technology at Instituto Politecnico Nacional both of them in Mexico. My Master's project was about simulations and calculation applied to Solid-state chemistry. When I finished my Master's degree I worked in the academic area and also in the Instituto de la Mujer (Women's Institute) in Mexico. In October 2020 I started my PhD at CISTIB where my project's name is Deep learning for multimodality multi-organ data fusion: Understanding cardiometabolic syndrome.
Job Titles:
- Research Software Engineer
Christopher Kelly is a research software engineer at CISTIB, in the school of Computing, University of Leeds. He completed his undergraduate and DPhil degrees in Engineering Science at the University of Oxford, where he worked at the BioMedIA cluster, Institute of Biomedical Engineering, working on image analysis methods for cardiac magnetic resonance imaging (MRI) data. In 2017 he moved to the Leeds Institute of Cardiovascular and Metabolic Medicine as a research fellow in Cardiovascular Imaging working on the analysis of diffusion tensor imaging in the heart. He joined the Research Software Engineering team at CISTIB in late 2020 where he works in two main projects, CardioX, a software solution for automated analysis of Cardiac MRI, and INSILEX, a software platform for facilitating in-silico trials.
Dr Blackman is a Consultant Interventional Cardiologist at Leeds Teaching Hospitals NHS Trust, and Honorary Clinical Associate Professor, specialising in interventional cardiology, and in particular transcatheter valve intervention
He qualified from the University of Birmingham in 1992, undertook research towards an MD at the University of Wales, Cardiff, and trained in general and interventional cardiology in Oxford and Toronto before being appointed as a Consultant in Leeds in 2005.
Dr Blackman built the trans-catheter valve intervention programme from scratch, undertaking the first TAVI procedure in Leeds in 2008. He has established Leeds as an international centre of excellence in trans-catheter valve intervention, at the forefront of new technologies and procedures. He has a personal reputation as a global leader in the field and has trained specialists across the UK, Europe, North America, and Asia in performing transcatheter valve interventions.
He is currently the Lead of the European Association of Percutaneous Cardiovascular Interventions (EAPCI) Valve for Life programme in the UK, and a member of the EAPCI Training & Education Group, and European Association of Cardiothoracic Surgery (EACTS) TechnoCollege faculty. As part of the NHS England Cardiac Services Clinical Reference Group, he advises NHS England on interventional cardiology services and is also a member of the NHS England Aortic Stenosis Policy Working Group and Structural Interventional Devices Group. He was Honorary Secretary of the British Cardiovascular Intervention Society from 2016-2020.
Research Interests: His main interests are in all aspects of trans-catheter valve intervention. This includes the study of novel devices in TAVI, in transcatheter mitral valve repair and replacement, and in trans-catheter tricuspid valve repair; evaluation of cerebral embolic protection devices to prevent stroke during TAVI; and investigation of optimal access route for TAVI procedures. He is a leading investigator in the study of long-term outcomes of TAVI devices, heading up the major UK and European studies. He has collaborated with other members of the CISTIB group, including Professor Greenwood to use Cardiovascular Magnetic Resonance to evaluate the outcomes of trans-catheter valve interventions, and is currently working with Professor Frangi on In-Silico studies of Transcatheter Aortic valve Implantation
Derek Magee is a lecturer in Computing at the University of Leeds with a research interest in medical image computing and machine learning, with a particular interest in Digital pathology image analysis. He has supervised 15 PhD students and numerous postdoctoral researchers since joining the university in 1997 and received funding from EPSRC, EU, CRUK, Wellcome Trust, Innovate Uk, LTH Charitable trust, and White Rose Health Innovation Partnership for projects as diverse as Interventional Ultrasound training systems, Cardiac image analysis, and developing digital pathology systems. He is currently involved in large projects relating to clinical adoption of digital pathology image analysis (NPIC - National Pathology Imaging Co-operative), and the use of image analysis in selecting patients for chemotherapy using digital pathology images. Additionally, he is supervisor of two PhD students for the Centre for Doctorial Training in AI in Medicine, as well as KTP associate in veterinary image analysis from video with company Vet-AI. In additional to his academic activities he is CTO and founder of HeteroGenius Limited (http://www.heterogenius.co.uk) a company producing software for management and analysis of digital pathology images. He has a strong record in commercialising academic research with software being licenced by ProZone limited for sports video analysis, and Cone beam-CT Quality Assurance system licenced by Modus QA.
Areas of expertise: Magnetic resonance imaging; MRI; heart; cardiac; diffusion; microstructure; tissue characterisation; pathology.
Dr Teh obtained his PhD in MRI Physics developing diffusion MRI methods at Imperial College London, UK (2009). He then took up postdoctoral appointments at the Agency for Science Technology and Research, Singapore (2009-12) and subsequently at the University of Oxford, UK (2012-16) where he focused on assessing the microstructure of the heart using diffusion MRI. Since 2017, Dr Teh joined the University of Leeds as a Senior Research Fellow and serves as the MRI Lead for the Experimental and Preclinical Imaging Centre (ePIC). The team at ePIC works extensively with partners to develop a wide range of MRI techniques and applications in the preclinical setting. Concurrently, there are strong connections with the clinic, and Dr Teh is involved in a number of clinical MRI studies that are being run at the Advanced Imaging Centre (AIC) and the Leeds General Infirmary. Dr Teh and the team are developing advanced diffusion MRI techniques for investigating the myocardial microstructure in both preclinical and clinical applications, funded by grants from the British Heart Foundation and Heart Research UK. These include the use of novel pulse sequences and computational modelling to deliver new biomarkers linked to myocardial structure and perfusion for assessing different patient groups.
Dr Jian Liu received his PhD in mathematics from UCLA, USA. He is currently a Lecturer of Neural Computation at the School of Computing, University of Leeds, UK. His research interests include fundamental questions of neural computation, computational neuroscience, and brain-inspired computation for artificial intelligence, as well as applications to robotics, medicine, and brain-machine interface.
Dr Zucker completed his BSc in Medical Sciences with Molecular Medicine at University College London (UCL) in 2009 undertaking research in mRNA expression of Flavin Containing Monooxygenase knockout mice. He continued at UCL to complete his undergraduate medical degree in 2012. During his time at UCL Dr Zucker worked as a research associate at the Centre for Evidence at Transplantation based at the Royal College of Surgeons conducting research into the rate of publication of randomised controlled trials in transplant medicine. He also undertook a Society for General Microbiology Studentship characterising the enzymatic properties of a previously unstudied bacteria implicated in cases of endocarditis.
Dr Zucker undertook his Foundation Training and Core Medical training in the Yorkshire region before being promoted early to the role of clinical oncology specialist registrar in 2016. During this time he was involved in a number of clinical research projects and had regular input in the management of patients enrolled in clinical trials. Dr Zucker took up his role as Clinical Research Fellow based at the Leeds Institute for Data Analytics in 2017 where he works on a number of projects including cancer outcome prediction, computer vision, natural language processing, data visualisation and process mining. Dr Zucker is also a Fellow of the Faculty of Clinical Informatics where he has co-founded the Early Career Group. He also sits on the Facultyàs Artificial Intelligence Specialist Interest Group and the Education and Training Subcommittee.
Responsibilities
Clinical Researcher
Center for Doctoral Training In Medical Artificial Intelligence Supervisor
LIDA Data Science Intern Supervisor
Research interests
Dr Zucker heads up the comorbidity and late effects workstream of the Macmillan funded Comprehensive Patient Records Project. This work aims to identify how pre-existing health conditions impact outcomes in the 20 most common cancer and how cancer and its treatment impact the long term health of patients. The research focuses on the analysis of large volumes of routinely collected health data including a linked dataset combining both primary and secondary care data. Dr Zucker has a particular interest in artificial intelligence methods and uses both traditional statistical approaches and machine learning in analytical approaches.
Dr Zucker is also the creator and lead developer of AuguR, a cancer analytics web application allowing clinicians to interact with real-world clinical data relating to oncology. This software is currently being rolled out across the Yorkshire and Humber Region. Dr Zucker also provides support to a range of other interdisciplinary projects across the university. Projects include automated image analytics for the diagnosis of Covid-19 from chest x-rays, automated reporting of cardiac MRI, process mining healthcare data, the development of interactive clinical outcomes dashboards, BRCA and breast cancer outcomes and health geography projects.
Bio: I am an Associate Professor at the School of Computing, University of Leeds, UK. My research focuses on robotic motion/manipulation planning and control. I am a co-chair of the IEEE-RAS Technical Committee on Mobile Manipulation and an Associate Editor for the IEEE Robotics and Automation - Letters (RA-L). Previously I was a postdoctoral researcher at CSAIL, MIT. I received my PhD in 2013 from the Robotics Institute at CMU.
Website URL: http://https://eps.leeds.ac.uk/computing/staff/743/dr-mehmet-dogar
Dr Michael Bryant CEng FHEA is an Associate Professor in Tribology and Corrosion Engineering in the Institute of Functional Surfaces (iFS), School of Mechanical Engineering. Current research focuses on: 1) streamlining preclinical testing methodologies, 2) the tribology and corrosion of metallic biomaterials (inc. nanoparticles) and 3) tribology and surface characterisation of biological tissues and soft matter materials. He has strong ties with industry, academic and regulatory (MHRA expert for tribology and corrosion & ASTM F04 committee member) groups. Research is currently funded as PI and Co-I through the EPSRC, Wellcome Trust, Royal Society, EU H2020 and Industry (> Ã £5.5m). He was awarded the IMechE Duncan Dowson Prize and Sir Thomas Hawksley gold medal in 2018.
Biography
Nishant Ravikumar is a Research Fellow at CISTIB, in the School of Computing, University of Leeds. He completed his PhD in 2017 at the University of Sheffield. Following this, he spent a couple of years as a postdoctoral researcher at the Pattern Recognition Lab, Friedrich-Alexander-University, Erlangen-Nuremberg. His previous work concentrated on shape registration and shape analysis, using probabilistic models. His current research interests are in developing algorithms that aid in the classification, segmentation and registration of medical images, for computer-aided diagnosis and interventions using machine learning.
Job Titles:
- Senior Research Fellow in the Leeds Institute of Health Sciences, School of Medicine
Expertise: health data science; electronic healthcare records; applied health research; prognostic models; statistical modelling; machine learning; parallel computing; linear algebra; numerical analysis
Research Interests: I'm interested in the application of cutting-edge statistical/AI methodologies to healthcare data, and particularly electronic healthcare records. This allows for the best possible solution to clinical research questions to be addressed using the large-scale healthcare data that is increasingly available for research from NHS Digital, CPRD, etc. This is particularly useful for questions where a clinical trial is infeasible or impossible. I am involved in a number of NIHR-funded projects across a wide variety of clinical areas including geriatrics (updating the electronic frailty index), mental health (investigating effect of service provision on re-attendance at the hospital), and musculoskeletal conditions. Previously I worked on batch linear algebra algorithms to dramatically improve the speed of, amongst other things, low-level operations required in modern machine learning software. These algorithms are currently used by NVIDIA, Intel, and ARM.
Areas of expertise: Bayesian statistics; data science; factor models; latent variable models; learning from multiple data sources; Spatio-temporal methods; topic modelling.
Research interests: My aim is to develop and apply statistical methods for targeting important real-world applications in various research fields including life sciences, health, urban analytics and natural language processing (NLP). I have a strong focus on combining information from multiple data sources using Bayesian Spatio-temporal latent variable modelling. I have recently worked on data integration for omics data, combining text-based data sources and streams for providing more interpretable insights and Spatio-temporal crime analysis.
Dr Toni Lassila received his doctorate in mathematics from Aalto University in 2010. He has previously worked at Ecole Polytechnique Federale de Lausanne in Switzerland. He joined CISTIB in August 2014 to work on image-based mathematical modelling in biomedical engineering problems. These include understanding the degeneration of brain tissue leading to dementia and modelling the behaviour of cardiac electromechanics in a pathological heart.
Research Interests
His research interests fall largely in the area of numerical methods for partial differential equations and cover various topics such as shape optimisation and shape sensitivity analysis, model reduction of parameterised nonlinear partial differential equations, and computational modelling of the cardiovascular system.
Dr Zhi-Qiang Zhang is an academic staff at the University of Leeds, where he holds a University Academic Fellow (UAF) position in Body Sensor Network for Healthcare and Robot between the School of Electronic and Electrical Engineering and School of Mechanical Engineering. He received his BEng degree in computer science from Tianjin University in 2005, and a PhD degree in Electrical Engineering from the University of Chinese Academy of Sciences in 2010. Upon completion of his PhD degree, he then moved to Imperial College London working as a research associate for five and half years.
After studying here at the University of Leeds, I graduated in 2019 with a BSc in Mathematics. During this time, I developed an interest in applied mathematics and numerical analysis, researching numerical algorithms for the simulation of physical systems in my final year project. In 2019, I joined the fluid dynamics CDT at Leeds, through which I became affiliated with CISTIB. My research involves the integration of physics-informed machine learning and medical imaging to improve left ventricular flow modelling.
Haoran Dou received his B.E. at Sichuan University, China in 2017. After that, He obtained his M.E. at the School of Biomedical Engineering, Shenzhen University. He is currently a PhD student in CISTIB supervised by Prof. Alex Frangi, Dr Nishant Ravikumar, and Dr Yan Xia.
Research Interest
His current research is mainly on deep learning in medical image computing.
I am Isuru Wijesinghe, a PhD candidate at the University of Leeds, School of Mechanical Engineering. My primary research interests lie in the broad areas of medical image analysis through deep learning in particular classification, segmentation, content-based image retrieval, and linear and non-linear optimization. In fact, I am expressly passionate about applying engineering principles in the field of Computer Science. I'm currently in my first year of PhD and my research is based on Intelligent Image-Driven Motion Management for Adaptive Precision Radiotherapy.
I hold a Degree in Master of Science (Major Component by research) of Engineering, specialized in Medical Image Analysis through Deep Learning from the University of Moratuwa. Additionally, I hold a Degree of Bachelor of the Science (Honours) of Engineering, specialized in Computer Science & Engineering from the University of Moratuwa.
During my MSc research, I have developed a prediction model to classify severity level of Diabetic Retinopathy using retinal images through an ensemble of deep CNNs and then extended this classification model to a content-based image retrieval model architecture to search the collections for retinal images that have characteristics similar to the case(s) of interest. Moreover, I've involved with two collaborative research projects, one is to detect wound boundaries of the diabetic patients through deep learning and the other project is to classify anomalies in Gastrointestinal-Tract through Endoscopic Imagery with deep learning. I have written several research papers during this time and they were accepted as full-paper oral presentations at 31st ICTAI in the USA, 28th ICANN in Germany, 19th BIBE in Greece and 05th Mercon in Sri Lanka. Moreover, I was fortunate to win a silver award at 21st National ICT AWARDS - NBQSA 2019 for my MSc research.
Prior to commencing my MSc studies, I have worked in the software industry. I did my undergraduate internship at Sysco LABS (Pvt) Ltd. I have worked at WSO2 Lanka (Pvt) Ltd as a Software Engineer for one year and as a Senior Software Engineer for another year. Then I have worked at Linear Squared (Pvt) Ltd as a Senior Data Engineer for one year.
Jack Breen completed an integrated Master's degree in mathematics (MMath) at the University of Nottingham in 2019. While working primarily in the field of statistics, Jack developed an interest in computational mathematics, and specifically for artificial intelligence.
Jack joined the CDT for Artificial Intelligence for Medical Diagnosis and Care as a PhD student in October 2020. His research focuses on diagnosing ovarian cancer, primarily using computer vision methods on histopathology slides. This work is supervised by Nishant Ravikumar of CISTIB, as well as Kieran Zucker, Nicolas Orsi and Geoff Hall from outside of CISTIB.
Lucy Godson completed a BSc. in Biochemistry with industrial experience at the University of Manchester (2018). During her undergraduate degree, she spent a year working on a clinical research project in a cancer immunology lab at the Mayo Clinic, Florida. Following this she carried out a final year project in computational biology, using machine learning to predict protein-protein interactions and protein functions in the model organism S. cerevisiae.
Lucy joined the CDT for Artificial Intelligence for Medical Diagnosis and Care, as a PhD student in October 2019. Her research involves predicting cancer patient outcomes through the integration and analysis of molecular, cellular and clinical data. She is co-supervised by Dr Ali Gooya and Professor Graham Cook.
Michael MacRaild graduated from the University of Manchester in July 2018 with a Masters degree in Mathematics and Physics (MMath&Phys). He then joined the EPSRC Centre for Doctoral Training (CDT) in Fluid Dynamics at the University of Leeds in October 2018. Michael completed an MSc in Fluid Dynamics with the CDT before joining CISTIB for his PhD, where he is supervised by Prof. Alex Frangi, Dr Toni Lassila and Dr Ali Sarrami Foroushani.
Research Interest
Michael's research focuses on developing efficient computational fluid dynamics simulation methods to facilitate in-silico clinical trials of endovascular medical devices. His main research areas include fluid dynamics, reduced order modelling, physics-informed neural networks and in-silico clinical trials.
Research Assistant at the University of Leeds, working in the Computational Imaging & Simulation Technologies in Biomedicine (CISTIB) with Professor Prof. Alejandro Frangi and Prof. Jurgen E Schneider on one of the BQ-Minded projects. His PhD is funded by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant and focussed on the characterization of brain tissue structure and vasculature using diffusion MRI. He received his M.Sc. in Biomedical Engineering from the Isfahan University of Medical Science under the supervision of Prof. Hossein Rabbani in 2016. Meanwhile, He worked as a graduate researcher at Medical Image and Signal Processing (MISP) research centre until September 2018. Before starting his PhD, his work has been devoted to various disciplines in signal/image processing such as Inverse Problem, Convex Optimization, and Signal Reconstruction.
Mr Fengming Lin received his B.S. degree in Communication Engineering in 2017 and the M.S. degree in Electronics and Communication Engineering in 2020, both from the School of Information Science and Engineering, Shandong University(Project 211, Project 985), China. His previous research work concentrates on brain tumour MRI segmentation based on deep learning. In September 2020 he joined the Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB) at the University of Leeds, UK as a PhD student supervised by Prof. Alex Frangi, Dr Nishant Ravikumar and Dr Yan Xia.
Nina Cheng graduated from Southern Medical University with a degree in Biomedical Engineering in 2017. She obtained a master's degree in Biomedical Engineering from Shenzhen University in 2020, and her research background is the automatic diagnosis of early Alzheimer's disease. In 2020, she joined CISTIB as a PhD student under the co-direction of Professor Alejandro Frangi, Dr Avan Suinesiaputra and Dr Nishant Ravikumar.
Research interest:
The latest project I am working on is the analysis of multi-modal cardiac images. My research interests include but are not limited to machine learning, deep learning, computer vision, etc.
Received her bachelor's degree in the Department of Computer Engineering at Yildirim Beyazit University in 2017. Starting from the last year of her undergraduate degree, she worked as a computer engineer in the state defence systems at Havelsan A.S. She received her master's degree in the MSc Data Science at the University of Sheffield in 2019. In 2020, she joined the CISTIB research group as a fully-funded PhD student supervised by Professor Alejandro Frangi.
Research Interests:
Her main research interest includes natural language processing and artificial intelligence applied to the medical domain.
Areas of expertise: Cancer Imaging; Radiomics; Image-guided Radiotherapy Planning; PET-CT; Nuclear Medicine; CT; MRI
I am a dual-certified Consultant in Radiology and Nuclear Medicine at Leeds Teaching Hospitals NHS Trust and an Honorary Professor of Radiology at the University of Leeds. I received my specialist training in Clinical Radiology in Oxford. Subsequently, I undertook a fellowship in Nuclear Medicine and PET-CT in Oxford and at St. Thomas's Hospital in London. I have been a Consultant in Leeds since October 2006 at one of the largest imaging departments in the UK.
I am academically active and my major research interests include the role of functional and molecular imaging in oncology. I have published extensively and lecture regularly at national and international meetings.
Job Titles:
- Professor of Artificial Intelligence at the University of Leeds
Areas of expertise: computer vision; machine learning
David Hogg is Professor of Artificial Intelligence at the University of Leeds. He is internationally recognized for his work on computer vision, particularly in the areas of video analysis and activity recognition. He works extensively across disciplinary boundaries, applying AI in engineering design, biology, medicine and environmental sciences. He has been a visiting professor at the MIT Media Lab, Pro-Vice-Chancellor for Research and Innovation at the University of Leeds (2011-2016), Chair of the ICT Strategic Advisory Team at the Engineering and Physical Sciences Research Council (EPSRC) in the UK, and Chair of an international review panel for Robotics and Artificial Intelligence commissioned by EPSRC (2017). Until 2018, he was Chair of the Academic Advisory Group of the Worldwide Universities Network (WUN), helping to promote collaborative research between over 20 prominent research-intensive universities from around the globe. He is Director of the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care; and a Co-Director of the Northern Pathology Imaging Co-operative. David is a Fellow of the European Association for Artificial Intelligence (EurAI), a Distinguished Fellow of the British Machine Vision Association, a Fellow of the International Association for Pattern Recognition, and a Turing Fellow.
Responsibilities
Director of Artificial Intelligence research theme
Job Titles:
- Professor ( Cardiology )
- Professor of Cardiology
Areas of expertise: Clinical applications of Cardiovascular Magnetic Resonance imaging; Percutaneous Coronary Intervention; Stable Coronary Artery Disease; Acute Coronary Syndromes; Myocardial infarction; Primary PCI
John Greenwood is a Professor of Cardiology in the Leeds Institute for Cardiovascular and Diabetes Research (LICAMM) and Consultant Cardiologist at Leeds Teaching Hospitals NHS Trust, where he specialises in coronary intervention and cardiovascular magnetic resonance (CMR) imaging.
He qualified in medicine from Leeds in 1991 and after general medical training in Yorkshire undertook a clinical PhD in Leeds, funded by the British Heart Foundation.
His main area of research is the diagnosis and treatment of stable and unstable coronary artery disease. In terms of diagnostics, this particularly involves the use of CMR in terms of its development and validation through clinical trials. He was Chief Investigator on the landmark CE-MARC trial (Lancet 2012) which compared the diagnostic accuracy, cost-effectiveness and prognostic ability of CMR and SPECT against X-ray angiography. He was also Chief Investigator of the BHF funded, CE-MARC II trial, a UK multi-centre, 3-way RCT comparing the management strategies of CMR vs. MPS-SPECT vs. UK NICE guidelines (CG95) for patients with stable chest pain. In terms of therapeutics, he is collaborating on a number of major multi-centre clinical trials designed to improve outcomes in patients undergoing primary PCI for acute ST-elevation myocardial infarction.
He is President-elect and Vice President (Education & Research) of the British Cardiovascular Society (BCS) and Chair of the BCS Scientific Programme Committee (2017-2020) and sits on BCS Council, BCS Board, and BCS Executive. He was elected to the Board of BSCMR (British Society of Cardiovascular MR) in 2009 and is now BSCMR President (2018-2020). He is past-Chair of the SCMR clinical trials committee (2015-2017) and was a member of the SCMR scientific programme committee (2016-2019). For 10 years Prof. Greenwood led the supra-regional CMR service in Leeds, one of the UK's largest, and as an interventional cardiologist actively contributes to the coronary intervention service for West Yorkshire, including the regional primary PCI service. He is Director of the Cardiovascular Clinical Research Facility at Leeds Teaching Hospitals NHS Trust.
Responsibilities
Director, Cardiovascular Clinical Research Facility (LTHT)
Prof. Jurgen E. Schneider, PhD, holds a Chair in Biomedical Imaging at the Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds and is Visiting Professor of Medical Imaging to the Radcliffe Department of Medicine, Division of Cardiovascular Medicine at the University of Oxford. He completed his PhD with Professor A. Haase at the University of WÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ¼rzburg in Germany in 2000 and relocated to Oxford in January 2001. He has been a major driving force nationally and internationally in the development and application of experimental cardiac magnetic resonance imaging (MRI) and spectroscopy (MRS) for rapid, non-invasive and comprehensive phenotyping of the rodent heart at ultra-high magnetic fields, and has published extensively in this field.
Until recently, Professor Schneider co-directed (jointly with Professors Stefan Neubauer and Craig Lygate), the British Heart Foundation Experimental Magnetic Resonance Unit (BMRU) in Oxford, where he was responsible for the development and application of experimental cardiac MR. Professor Schneider's role was central to multiple internal and external cardiovascular research projects within the department and beyond. In 2016 he accepted a personal chair in Leeds and is now directing the recently opened Experimental and Preclinical Imaging Centre (ePIC), which provides access to the latest generation of multi-modal imaging equipment, including MRI (7 Tesla), PET / SPECT / CT, optical imaging, ultrasound and à à à à à à à à à à à à à à à à ¼CT, and, together with Prof Sven Plein, co-directs the clinical Advanced Imaging Centre (AIC).
Responsibilities
Director, Experimental & Preclinical Imaging Centre (ePIC)
Professor Richard Hall resides in the School of Mechanical Engineering where he delivers research in the areas of medical engineering focused on the spine and hip particularly with a focus on pre-clinical in vitro assessments including wear simulation. He has an undergraduate degree in Physics from the University of Leeds and was awarded a PhD from the University of Lancaster. He has had research funding from the EU (LifeLongJoints, SpineFX, Biotrib and Nu-Spine) as well as the UKRI and NIH in the USA. He has international collaborations with leading researchers including those at Uppsala, Sweden; ETH Zurich, Switzerland; TUHH, Germany and STU, Australia which have within them significant industrial clinical and partners.
Job Titles:
- Associate Professor at the University of Leeds
Ryan Mathew is an Associate Professor at the University of Leeds (UoL) and Honorary Consultant Neurosurgeon at the Leeds Teaching Hospitals NHS Trust (http://www.leedsneurosurgery.com). He obtained an MBChB with Honours and an intercalated BSc with Honours, the latter in Clinical Sciences (Tissue Engineering) research. During his neurosurgical training/residency, he undertook further basic science research (funded by Cancer Research UK) into brain cancer and was awarded a PhD based on Glioma Modelling using induced Pluripotent Stem Cells (iPSCs) and Cerebral Organoids. He subsequently spent time as a Visiting Research Collaborator at the Brain Tumour Research Centre at Sickkids in Toronto.
His research interests include basic and translational research into brain cancer, preclinical model development, medical devices, surgical technologies and immersive. At the University of Leeds, he co-leads the Stem Cells and Brain Tumour Group with Dr Heiko Wurdak (http://www.braincancer.leeds.ac.uk/stem-cells-and-brain-tumour-research-group/), he is Academic Lead for Health and Wellbeing at the Centre for Immersive Technologies (https://www.leeds.ac.uk/info/130571/centre_for_immersive_technologies), Neurosurgical Lead for the National Institute of Health Research (NIHR) Surgical MedTechCooperative (https://surgicalmic.nihr.ac.uk/about-us/meet-the-team/), Neurosurgical Lead and Steering Committee Member of the Leeds Institute of Clinical Trials Research and was recently part of the successful bid to become an NIHR Academy Advanced Surgical Technology Incubator (a joint initiative between Leeds and UCL). He is passionate about research public engagement and was awarded a Flame of Hope for Research Engagement by Cancer Research UK.
He has a clinical subspecialist interest in all types of brain tumours, with a special focus on glioma, meningiomas and awake surgery. He is Co-Lead for Medical Research Council (MRC) Brain Tissue Liaison for the Society of British Neurological Surgeons (SBNS) Academic Committee https://www.sbns.org.uk/index.php/research/academic-neurosurgeons/), and a member of the National Cancer Research Institute s Glioma Subgroup.
Job Titles:
- Professor of Ultrasonics and Embedded Systems
Areas of expertise: ultrasonics; embedded systems
Steven Freear earned his doctorate in 1997 and subsequently worked in the medical industry for seven years as an electronic system designer. He was appointed Assistant Professor, Associate Professor and then Professor with the School of Electronic and Electrical Engineering at the University of Leeds, Leeds, UK., in 2006, 2008 and 2016 respectively, where he is currently Director of Research and Innovation. In 2006, he formed the Ultrasound and Embedded Systems Group, specializing in both industrial and biomedical research. His main research interest is concerned with advanced analog and digital signal processing and efficient embedded systems design. He teaches digital signal processing, VLSI and embedded systems design, and hardware description languages at both undergraduate and postgraduate levels. He is Vice President for Publications for the IEEE Ultrasonics, Ferroelectrics and Frequency Control Society (UFFC) having previous served as Editor-in-Chief of the Transactions on UFFC (2013-2018). He was Visiting Professor at Georgia Tech from 2014-2018 where he led the development of the imaging engine for an MRI compatible CMUT intravascular catheter funded by NIH/Siemens. His research group has developed the Ultrasound Array Research Platform (UARP); its associated intellectual property (IP) is widely used on several biomedical and industrial research projects, both internally and throughout the UK. Relevant EPSRC supported research includes: EP/I000623/1 and EP/P023266/1 which make use of the UARP for imaging and the targeted acoustic delivery of chemotherapy agents (the UARP is currently under trial with project partner Medical Discoveries Catapult). Grants EP/N034813/1 EP/K029835/1 reflect novel transducer development making use of metamaterials. We have extensive industrial experience and recently gained an R&D contract to deploy the UARP at the nuclear decommissioning company, Sellafield, as part of their live decommissioning programme. The group's embedded systems magnetometry work was developed and commercialized with Speir Hunter. Our patented technology (WO2013/128212, WO/2013/128210, WO2018046947A) is now exploited globally by National Grid (UK), Shell (USA & Canada), Enbridge (Canada), Total (France), Gasunie (Netherlands & Germany), Sinopec (China & Malaysia), GRTgaz (France) and Petrochina (China), inter-alia. We have completed 4 highly successful Industrial Knowledge Transfer Partnership projects with Pace, RTK Instruments, BCA leisure, Ardent and currently, have embarked on two further projects with Oil and Gas Measurements and LBBC Group. The group has a research portfolio in excess of à £6.2m, 9 patents and over 200 publications.
Job Titles:
- Professor of Cardiology ( Clinical )
Areas of expertise: Biomedical Imaging; Cardiology; Cardiovascular disease; Magnetic Resonance Imaging
I am a Professor of Cardiology and British Heart Foundation Professor of Cardiovascular Imagin at the University of Leeds, where I have led the Department of Biomedical Imaging Science since 2017. In addition, I hold an honorary Consultant Cardiologist contract at Leeds Teaching Hospitals NHS Trust in Leeds. I studied Medicine in Marburg/Germany and received an MD from the Phillips University in Marburg/Germany in 1995 and my PhD from the University of Leeds in 2004. I was previously a British Heart Foundation Senior Clinical Research Fellow (2011-2015), Wellcome Trust Intermediate Research Fellow (2006-2010) and British Heart Foundation Junior Research Fellow (2001-2003). I have held several societal positions including Vice presidency European Association of Cardiovascular Imaging (EACVI) of the European Society of Cardiology, Chairman of the Working Group on Cardiovascular Magnetic Resonance Imaging of the European Society of Cardiology and serve on several editorial boards including Senior Associate Editor European Heart Journal Cardiovascular Imaging. My grant income includes a British Heart Foundation programme grant. Mechanisms of cardiovascular disease in diabetes Mellitus and I have published over 250 original research, review and position papers.
Responsibilities
Head of Department of Biomedical Imaging Science
Job Titles:
- Associate Editor of IEEE Trans
- Professor of Biomedical Image Computing at the University of Sheffield
- Research Assistant at Im - Lab
- Research Interests
Alejandro (Alex) Frangi was born in La Plata, Argentina. In 1991 he moved to Barcelona, Spain, where he obtained his undergraduate degree in Telecommunications Engineering from the Technical University of Catalonia (Barcelona) in 1996. He subsequently carried out research on electrical impedance tomography for image reconstruction and noise characterization at the same institution under a CIRIT grant. In 1997 he obtained a grant from the Dutch Ministry of Economic Affairs to pursue his PhD at the Image Sciences Institute (www.isi.uu.nl) of the University Medical Center Utrecht on model-based cardiovascular image analysis. During this period he was visiting researcher at the Imperial College in London, UK, and in Philips Medical Systems BV, The Netherlands.
Dr Frangi is Professor of Biomedical Image Computing at the University of Sheffield (USFD), Sheffield, UK. Before, he was Associate Professor at Universitat Pompeu Fabra (UPF) and ICREA-Academia Researcher (www.icrea.cat). He currently leads the Center for Computational Imaging & Simulation Technologies in Biomedicine (www.cistib.org). CISTIB is part of INSIGNEO Institute for in silico Medicine, a joint initiative between USFD and the Sheffield Teaching Hospitals Foundation Trust to realise the scientific ambition behind the Virtual Physiological Human (VPH), producing a transformational impact on healthcare. His main research interests are in medical image computing, medical imaging and image-based computational physiology.
Prof Frangi has been principal investigator or scientific coordinator of over 20 national and European projects, both funded by public and private bodies. During 1/2006-3/2010 he was coordinator of the @neurIST (www.aneurist.org), a European Integrated Project, during 1/2006-12/2009 he was scientific co-PI for the Spanish CENIT Technology Platform CDTEAM (www.cdteam.org) funded with by the Spanish Ministry of Science and Innovation through CDTI, in 2009-2012 he took part of the euHeart (www.euheart.eu) Integrated Project, in 2009-2012 in the Virtual Physiological Human Network of Excellence (www.VPH-noe.eu), and in 2009-2012 he was Scientific Coordinator of the CENIT Technology Platform cvREMOD (www.cvremod.com) funded with by the Spanish Ministry of Science and Innovation through CDTI. He recently was awarded a funding from the European Commission as coordinator entitled VPH-DARE@IT DementiA Research Enabled by IT (www.vph-dare.eu), led by the University of Sheffield together with other 19 European organizations.
Prof Frangi has edited a book, published 6 editorial articles and over 125 journal papers in key international journals of his research field and more than over 170 book chapters and international conference papers with an h-index 25 and an average number of citations per paper over 15.9 according to ISI WoK. He has been three times Guest Editor of special issues of IEEE Trans Med Imaging, one on IEEE Trans Biomed Eng, and one of Medical Image Analysis journal. He was chair of the 3rd International Conference on Functional Imaging and Modelling of the Heart (FIMH05) held in Barcelona in June 2005, Publications Chair of the IEEE International Symposium in Biomedical Imaging (ISBI 2006), Programme Committee Member of various editions of the Intl. Conf. on Medical Image Computing and Computer Assisted Interventions (MICCAI) (Brisbane, AU, 2007; Beijing CN, 2010; Toronto CA 2011; Nice FR 2012; Nagoya JP 2013), International Liaison of ISBI 2009, Tutorials Co-Chair of MICCAI 2010, and Program Co-chair of MICCAI 2015. He was also General Chair for ISBI 2012 held in Barcelona.
Prof Frangi is Associate Editor of IEEE Trans on Medical Imaging, Medical Image Analysis, SIAM Journal Imaging Sciences, Computer Vision and Image Understanding, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization and Recent Patents in Biomedical Engineering journals. Prof Frangi was foreign member of the Review College of the Engineering and Physical Sciences Research Council (EPSRC, 2006-10) in the UK, is a recipient of the IEEE Engineering in Medicine and Biology Early Career Award in 2006, the Prizes for Knowledge Transfer (2008) in the Information and Communication Technologies domain and of Teaching Excellence (2008, 2010) by the Social Council of the Universitat Pompeu Fabra. He also was awarded the UPF Medal (2011) for his service as Dean of the Escuela Politecnica Superior. He was awarded the ICREA-Academia Prizes awarded by the Institucio Catalana de Recerca i Estudis Avancats (ICREA) in 2008. Finally, Prof Frangi is IEEE Fellow (2014), SPIE Member, SIAM Member, MICCAI Member, and elected member to the Board of Directors of the Medical Image Computing and Computer Assisted Interventions (MICCAI) Society (2014-2018). Prof Frangi has been selected as a Highly Cited Researcher in the field of Engineering by Thomson Reuters having 3 highly cited papers according to the Essential Science Indicators by the same organisation.
David is Bowel Cancer UK & RCS Engl. Professor of Surgery at the University of Leeds and Hon. Consultant Surgeon at LTHT. His clinical interests include robotic and minimally invasive surgery. He is Chief Investigator for several NIHR portfolio clinical trials, including MRC/EME/NIHR ROLARR, HTA/NIHR FIAT, HTA/NIHR SaFaRI, and MRC/EME/NIHR IntAct. He is Clinical Director of the Leeds NIHR MIC in Surgical Technologies, the Leeds RCS Eng. Surgical Trials Centre, and Co-Director for the Centre for HealthTech Innovation.
Job Titles:
- Research Assistant at Im - Lab
- Research Interests
I completed my BSc (2014) and MSc (2015) in Physics at Instituto Balseiro, Bariloche (Argentina). From 2017 to 2019 I worked as a research assistant at Im-Lab (University of Chicago) within the field of statistical genetics, our main interest being to unravel the biological mechanisms linking genetic variants with complex traits.
In September 2019 I joined CISTIB as a PhD student, with Prof. Alejandro Frangi as supervisor, where I will study the genetic basis of image-derived phenotypes, from cardiovascular magnetic resonance (CMR) images and also other modalities.
Research Interests:
Machine learning, deep learning, genetics of complex traits, genomics, medical image analysis.
After graduating from the University of Glasgow with first-class honours in mathematics, I joined the Fluid Dynamics CDT at Leeds in 2020. I was immediately attracted to the biomedical applications of fluid dynamics, and my first year MSc team project investigated the validity of the Clauser plot method for measuring wall shear stress in preclinical models of cardiovascular disease.
My project is aimed at creating models of multiscale fluid transport for characterising treatment response in tumours. I am supervised by Zeike Taylor, David Buckley and Ali Gooya, starting in summer 2021.
I am a clinical scientist working at Leeds Teaching Hospitals Trust and an NIHR research fellow. My research interests are in using cardiac computational models to improve catheter ablation outcomes to treat patients with atrial fibrillation.
Shokoufeh Golshani completed her undergraduate studies double majoring in Biomedical and Electrical Engineering at the Amirkabir University of Technology (AUT), Iran. She subsequently continued her studies in Advanced Medical Imaging Research Lab (AMIR Lab) at the same institute and received her Masteràs degree in biomedical Engineering in 2014. Her research focus was on improving the speed and quality of strain imaging through cardiovascular magnetic resonance polar tagging. The outstanding results were published in 5 international conference papers and one MRM journal paper. Her abstract entitled à Efficient Radial Tagging: Undersampled Radial Acquisition with Polar Fourier Transform Reconstructionà was awarded the ISMRM Magna Cum Laude Merit Award. In collaboration with her supervisor, Dr. Abbas Nasiraei Moghaddam, she have published a US patent application. During her master, she also gained precious teaching experience through instructing the Electric Circuit & Measurement Laboratory and Electronic Circuits Laboratory courses (undergraduate courses) and working as a teacher assistant in Cardiovascular Biomechanics course (graduate course) in consecutive semesters.
Currently, she has been awarded a Marie Curie Early Stage Researcher scholarship in the BQ-Minded project, an international research project on quantitative magnetic resonance imaging funded by the European Unionàs Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement. She joined the Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB) at the University of Leeds, UK, as a research assistant in 2019. She has begun her Ph.D. studies jointly in the school of computing and the school of medicine under the supervision of Prof. Alejandro Frangi and Prof. Jurgen Schneider. The main aim of her current project is to accelerate diffusion MRI measurements using state-of-the-art hardware- and software-based methodologies.
Received his B.S. degree in Electronics and Information Engineering in 2016 and the M.S. degree in Communication and Information System in 2019, both from Sichuan University, Chengdu, China. He has acted as the main participant in several projects in the areas of artificial intelligence (e.g., Identification of Unsound Kernels in Wheat). He was a member of the Image Information Institute of Sichuan University during his postgraduate studies. He joined the CISTIB research group at the University of Leeds as a PhD student in September 2019 supervised by Prof. Alejandro Frangi and Dr Ali Gooya.
Research interests:
His main research interest includes machine learning, deep learning, computer vision, image synthesis, medical image registration and medical image analysis.