Panel Session

Panel Title

Transforming Medical Imaging with AI: Challenges, Data & Infrastructure, Advancing Research, and Translating Innovations

Mediators: Duygu Sarikaya, Nashid Alam and Luisa Cutillo

Panel Description

Artificial intelligence is rapidly reshaping the landscape of medical imaging—from early diagnosis and segmentation to image reconstruction and clinical decision support. However, realizing the full potential of AI in this domain requires coordinated efforts across multiple fronts: overcoming technical and regulatory challenges, building robust data ecosystems and computational infrastructure, advancing and funding cutting-edge research, and ensuring successful translation into real-world clinical workflows.

This interdisciplinary panel brings together leading experts in medical image analysis, research and invitations to discuss:

Current challenges in deploying AI in medical imaging, including data quality, generalizability, bias, interpretability, and regulatory hurdles.

Data and infrastructure needs, including secure data sharing frameworks, federated learning, multimodal integration, and scalable computing platforms.

Funding opportunities and grant schemes that are shaping the next generation of research covering national and international programs supporting translational AI, strategic investments in infrastructure and interdisciplinary collaboration.

Pathways to translation, exploring how to move innovations from lab to bedside, foster clinical adoption, and evaluate impact on patient outcomes.

Attendees will gain insights into emerging trends, current funding landscapes, and actionable strategies to accelerate the safe and effective integration of AI into medical imaging pipelines.

Susan Astley Theodossiadis (Chair)

Professor of Intelligent Medical Imaging, The University of Manchester

Sue’s work is focused on the development and evaluation of imaging biomarkers for breast cancer risk, and the science underpinning stratified screening. Her research encompasses a range of technologies both for breast density measurement and early detection of cancer. Projects include the use of AI to predict cancers and to assess breast cancer risk from standard and ultra-low-dose mammograms, assessment of breast cancer risk in Saudi Arabia, evaluation of the impact of computer aided detection on reader behaviour and performance, reader variability studies, and the use of contrast enhanced mammography for evaluation of breast lesions. Her work is collaborative within a multidisciplinary network of scientists and clinicians in the UK and overseas. Sue started out as an astronomer and cosmic ray physicist before developing an interest in computation and medical imaging.

Bogdan Matuszewski (Co-chair)

Professor of Computer Vision, School of Engineering and Computing, University of Central Lancashire

Bogdan’s research over the years has covered core computer vision challenges, including segmentation, registration, classification, tracking, 3D reconstruction and pose estimation, as well as uncertainty quantification in machine learning. More recently, his interests have shifted to the use of mixed-modality generative models in reinforcement learning. His work in biomedical applications includes well-being technologies, histopathology image analysis, radiotherapy planning and monitoring, and endoscopy automation.

He has supervised 21 PhD students to successful completion. Currently, he serves as Deputy Director of the Institute for Engineering and Technology Innovation (InETI) and Head of the Computer Vision and Machine Learning (CVML) Group

Fredrik Andreas Dahl

Senior Research Scientist, Norwegian Computing Centre, Norway

Dr Dahl has a PhD in neural net-based machine learning (2001) and 16 years' experience in medical statistics and patient flow modelling. Dr Dahl and his team are in the process of evaluating the commercial potential of their mammography model, and hence he has some insight into the regulatory hurdles in this area as well. He is also involved in a project where he and his team are using AI to automatically dispatch patient referrals to the appropriate section in the orthopaedic clinic. Here they are collaborating with the EHR vendor.

Shahid Farid

Consultant general, hepatobiliary and liver transplant surgeon, NHS Trust, UK

Dr Farid is a highly accomplished and internationally renowned Consultant Surgeon working at St. James’s University Hospitals. He is director of Clarity Health Consultancy providing strategic direction to industry in developing med-tech platforms in the NHS. He is also faculty member of the National Organ Retrieval Service Masterclass Training group.

Claudia Lindner

Senior Research Fellow and Sir Henry Dale Fellow in Translational Medical Imaging, University of Manchester

Dr Claudia Lindner is a Senior Research Fellow and Sir Henry Dale Fellow in Translational Medical Imaging at The University of Manchester. Her career includes over 20 years of international experience in the development and application of computational methods, working within multi-disciplinary teams in both industrial and academic settings. Claudia uses methods from computer vision, machine learning and data science to develop automatic systems for analysing structures in medical images, with a particular focus on musculoskeletal applications (https://bone-finder.com). She has published over 50 peer-reviewed papers, and is dedicated to impactful research, actively advancing her work towards real-world solutions. In her role as the Translation Lead for the Christabel Pankhurst Institute for Health Technology Research and Innovation, Claudia directs her efforts towards facilitating the translation of research findings into benefits for society and leads the development of the Pankhurst Health Technology Translation Toolkit (https://translation-toolkit.manchester.ac.uk).

Bharat Pokhrel

Research Development Manager, University of Leeds

Dr Bharat Pokhrel is a Research Development Manager at the University of Leeds. Bharat holds a PhD in Molecular and Cellular Biology and has a background in biology, biochemistry and biotechnology. At Leeds, he leads the co-ordination of development of high-value research and innovation proposals in engineering and physical sciences, working closely with academics, funders, and industry partners. His role focuses on shaping strategic funding opportunities, fostering cross-sector collaborations, and supporting capability building across the University.

Prior to this, Bharat worked at the Engineering and Physical Sciences Research Council (EPSRC) as a Portfolio Manager, overseeing national research portfolios and supporting strategic investments. He brings experience in funding policy, research strategy, stakeholder engagement, and peer review. Bharat is passionate about enabling impactful research and supporting environments where innovation can thrive.

Aaron Quyn

Colorectal Surgeon and Academic, University of Leeds

Prof Aaron Quyn is a colorectal surgeon and academic at the University of Leeds, specializing in advanced rectal cancer. He co-leads the POLARIS trial and plays a key role in surgical innovation and trials through the NIHR Surgical MedTech Co-operative and the Leeds RCS England Trials Centre.

Gui Tran

Harrogate and District Foundation Trust Hospital

Dr Tran is a Consultant Rheumatologist and Lead for Innovation at Harrogate and District Foundation Trust Hospital. He is also Outpatient Clinical Lead for the hospital, as well as West Yorkshire and Humber and North Yorkshire. This encompasses 9 hospital trusts treating a population of over 5 million people. His roles include delivering, scaling and embedding innovations into the healthcare pathways to improve all healthcare outcomes