Organiser & chair: Julia Schnabel
Abstract:
This session explores the critical “R4” challenges—Reconstruction, Resolution, Regularization, and Representation—that are central to advancing medical imaging technologies. With a strong focus on how novel computational methods, including machine learning and physics-informed techniques, can address longstanding limitations in image quality, acquisition time, and motion artifacts, this session highlights innovative approaches across a range of medical imaging modalities, including MRI, PET, and photoacoustic tomography (PAT), demonstrating synergistic opportunities for overcoming common imaging challenges.
