This two-day symposium on March 9-10 2026, featuring invited internationally-leading researchers covering recent advances in AI and image reconstruction for biomedical imaging, is intended to enhance UK and international networking, research progress and education in this important area. The symposium is part of the EPSRC funded computational collaborative project in synergistic reconstruction in biomedical imaging (SyneRBI).
The symposium will also include a dedicate session on the PET Rapid Image Reconstruction Challenge 2 (PETRIC2).
We have an exciting line up of invited speakers attending from across the globe, including: Charles Bouman (Purdue), Alexandre Bousse (Brest), Hyungjin Chung (EverEx), Joyita Dutta (UMass), Florian Knoll (FAU Erlangen), Erich Kobler (Linz), Abolfazl Mehranian (GE Healthcare), Jae Sung Lee (Seoul), Jinyi Qi (UC Davis), Julia Schnabel (TU Munich), Carola Schönlieb (Cambridge) Julian Tachella (CNRS, Lyon), Andrew Wang (Blur Labs), Guobao Wang (UC Davis)
Organising committee
A. J. Reader (King’s College London), D. Atkinson (University College London), M. Ehrhardt (University of Bath), C. Kolbitsch (Physikalisch-Technische Bundesanstalt), J. C. Matthews (University of Manchester), E. Pasca (Science & Technology Facilities Council), A. Tavares (University of Edinburg), K. Thielemans (University College London), C. Tsoumpas (University of Groningen) .
Location
Programme
Day 1 Programme
| Time | Speaker | Title / Description |
|---|---|---|
| 8:15 | Registration (and set up of poster session 1) | |
| 9:00 | Welcome, introduction to day 1 | |
| 9:30 | Guobao Wang | Bridging Physics and Learning: A Decade of Kernel Methods for Image Reconstruction |
| 10:00 | Hyungjin Chung | Test-time adaptation in diffusion models for medical image reconstruction |
| 10:30 | Zekai Li | Hybrid kernelised PET reconstruction allowing for negative values |
| 10:45 | George Webber | A Non-Overfitting Objective for PET Image Reconstruction |
| 11:00 | COFFEE BREAK (Poster session 1 posters visible) | |
| 11:30 | Florian Knoll | Exploring the limitations of deep learning for MR image reconstruction |
| 12:00 | Julia Schnabel | Self-supervised motion reconstruction for precision MR(A)I |
| 12:30 | Natascha Niessen | INR meets Multi-Contrast MRI Reconstruction |
| 12:45 | Jelmer van Lune | Physics-Guided Reconstruction of Quantitative MRI from Conventional Contrasts by Self-Supervised Deep Learning |
| 13:00 | LUNCH — POSTER SESSION 1 (14 posters) | |
| 14:30 | Charles Bouman | Generative plug-and-play for medical image reconstruction |
| 15:00 | Erich Kobler | DEALing with Image Reconstruction: Deep Attentive Least Squares |
| 15:30 | Evangelos Papoutsellis | Why do we regularise in every iteration for imaging inverse problems? |
| 15:45 | Alessandro Perelli | Stochastic Multiresolution Image Sketching for Inverse Imaging Problems |
| 16:00 | COFFEE BREAK (Poster session 1 posters visible) | |
| 16:30 | Simon Arridge | Inverse Problems in Radiative Transport |
| 17:00 | Joyita Dutta | AI for post-reconstruction medical image enhancement |
| 17:30 | Zi Wang | Physics-Informed Synthetic Data Learning: Boosting Multi-Scenario Fast MRI Reconstruction with Only One Model |
| 17:45 | Yi Li | Deep Learned Beamforming for Coherent Multi-Transducer Ultrasound Systems |
| 18:00 | End of day — Posters from session 1: please remove posters | |
| 19:00 | Reception drinks outside the Great Hall | |
| 19:30 | DINNER AT THE GREAT HALL (Strand Campus, Strand, London, WC2R 2LS) | |
Day 2 Programme
| Time | Speaker | Title / Description |
|---|---|---|
| 9:00 | Registration (and poster session 2 setup) | |
| 9:20 | Introduction to day 2 | |
| 9:30 | Jinyi Qi | Image reconstruction for positronium lifetime tomography |
| 10:00 | Carola Schönlieb | AI for medical image reconstruction and the challenges of hallucinations |
| 10:30 | Corentin Constanza | Unrolled MAPEM for SPECT reconstruction |
| 10:45 | Movindu Dassanayake | List-Mode Data Derived Synthetic PET Image Reconstruction |
| 11:00 | COFFEE BREAK (Poster session 2 posters visible) | |
| 11:30 | Alexander Bousse | Unsupervised Learning for CT and PET Reconstruction with Generative Models |
| 12:00 | Daniel Sanderson | Decomposed Diffusion Reconstruction for Multiple Artifact Correction in Computed Tomography Imaging |
| 12:15 | Sam Porter | Accelerating Joint PET/SPECT/CT Reconstruction with Synergy-Aware Preconditioning and Variance Reduction |
| 12:30 | LUNCH — POSTER SESSION 2 (14 posters) | |
| 14:00 | Jae Sung Lee | The evolving roles and perspective of AI in nuclear medicine |
| 14:30 | Georg Schramm | Recommendations on the Use of Artificial Intelligence in Image Reconstruction in Radiology and Nuclear Medicine |
| 15:00 | Abolfazl Mehranian | AI Advances in Quantitative Molecular Imaging: An Industrial Perspective |
| 15:30 | COFFEE BREAK (Poster session 2 posters visible) | |
| 16:00 | Julian Tachella | Equivariant Splitting: Self-supervised learning from incomplete data |
| 16:30 | Andrew Wang | Get started with DeepInverse for image reconstruction with deep learning |
| 16:50 |
PET Rapid Image Reconstruction Challenge 2 (PETRIC2) | |
| 17:50 |
Closing remarks | |
| 18:00 | End of day — Posters from session 2: please remove posters (CLOSE) | |
POSTERS DAY 1
| Name | Poster Title |
|---|---|
| Arratia, Pablo | Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI |
| CHIN, SHIH YUN | Metal Artifact Correction for Cone-Beam CT Images Based on Deep Learning |
| Du, Yuning | Active Sampling for MRI-based Sequential Decision Making |
| Hawkins, Clara | Multi-modality imaging techniques for X-ray Fluorescence and Ptychography |
| Jameel, Usama | Cross-Domain Transformer-Diffusion Framework for Clinical-Grade Reconstruction of Low-Dose CT Sinograms |
| Khan, Muhammad | Tomographic Reconstruction with Real-time a priori Acquisition |
| Mehrabi, Mohsen | Unrolled Networks for MRI Reconstruction: Hybrid Learning for Superior Performance in Low-SNR Data |
| Mousavi, Seyyed Mahmoud | An Open-Source Benchmark for Modular PET Reconstruction: Establishing a Baseline for STIR and CASToR |
| Sabir, Amin | Advanced image reconstruction methods for light-sheet microscopy |
| Taheri, Nasrin | Can We Trust Self-Supervised PET Reconstruction Without Controlling the Randomness? |
| Ur Rahman, Atiq | Data-driven mapping of proton radiographs to water-equivalent path length |
| Wong, Hok Shing | A Stochastic Three Operator Splitting Algorithm for Inverse Problems |
| Yang, Liutao | Anatomically Conditioned Implicit Network for Low-Dose PET Reconstruction and Super-Resolution |
POSTERS DAY 2
| Name | Poster Title |
|---|---|
| Biguri, Ander | Current Progress on LION v0.2: Deep Learning Library for Computed Tomography |
| Dao, Viet | Automated Data Driven Motion Detection, Estimation and Correction for Positron Emission Tomography |
| Golbabaee, Mohammad | MRI2Qmap: multiparametric quantitative MRI reconstruction using learned spatial priors from multimodal MRI datasets |
| Hsu, Hsin-Yun | Deep Learning-Based Image Reconstruction for Small Animal PET |
| Jayaraj, Aparna | Scatter Correction for Long Axial Field of View Scanners in STIR Library |
| Klimaszewski, Konrad | Event-Level Machine Learning for Comprehensive PET Coincidence Correction |
| Modrzyk, Thibaut | Convergent Plug-and-Play reconstruction for Poisson inverse problems with application to emission tomography |
| Prokopenko, Denis | Deep Learning Reconstruction for Dynamic Fetal Cardiac MRI |
| Sainz Bear, Andrea | FusionFBP and DeepFusionBP: Novel Combinations of Deep Learning and Filtered Backprojection |
| Shopa, Roman | Multi-Photon Detector Blur Estimation in Total-Body Modular PET Scanners |
| Trinh, Minh Nhat | Napari-ToMoDL: An Open-Source and User-Friendly Napari Plugin for High-Performance Tomographic Reconstruction |
| Webber, George | Advances in Diffusion-Model-based PET Image Reconstruction |
| Xu, Zihan | Fast latent diffusion model for 3D reconstruction using symmetry breaking |
Submissions
Submissions are now closed. Please note that papers presented at the symposium could be submitted to the Frontiers in Nuclear Medicine, research topic: Rapid Image Reconstruction.
Registration
Registration for online attendance in open. Registration for in person attendance is closed.
Satellite Hackathons
Associated to the AI-RBI symposium, there will be two hackathons, requiring separate registration. Please check their dedicated web-pages for more information:
- STIR Hackathon 2026, 5-6 Mar 2026.
- Hackathon on software for machine learning approaches in biomedical imaging, 11-12 March.
Further Information
Please check the current page for latest information.