Thank you
Thank you to our invited speakers and to everyone who joined us in Philadelphia or online. The workshop brought together researchers, clinicians, and imaging scientists to discuss deep learning methods for image formation, analysis, and evaluation across medical imaging modalities.
The workshop received 471 registrations from 29 countries. We are also grateful for support from Penn Radiology and our sponsors for making the meeting possible.
The agenda, with links to the recordings, is below. View the full YouTube playlist.
Introduction
The workshop provided a multidisciplinary forum for exchanging ideas on deep learning methods for image formation, analysis, and evaluation across CT, nuclear medicine, MRI, ultrasound, and optical imaging. Invited presentations reviewed the state of the art and explored potential future research directions.
View the archived event website.
Agenda
Friday, July 17
Registration
Welcome and opening remarks
Grace J. Gang, PhD, and Pari V. Pandharipande, MD, MPH · University of Pennsylvania
Can We Assess Imaging Quality in the AI Era?
Mitchell Schnall, MD, PhD · University of Pennsylvania
Task-Based Evaluation of Neural Network Reconstruction in MRI
Angel Pineda, PhD · Hofstra University
Computational Bio-Imaging via Inverse-Scattering
Shwetadwip Chowdhury, PhD · The University of Texas at Austin
Physics- and Learning-Based Sparse Phase Reconstruction of Holographic Lens-Free Images
Rene Vidal, PhD · University of Pennsylvania
Break
AI-Powered Fast, Low-Dose PET/MRI for Precision Radiotherapy
Xiaofeng Yang, PhD, DABR · University of Chicago
Hallucinations in Medical Devices
Jason Granstedt, PhD · U.S. Food and Drug Administration
From Pixels to Poses: Deep Learning and Physics-Guided Adaptive Image Formation for Spine Ultrasound
Emad Boctor, PhD · Johns Hopkins University
Clinical Needs for Improvements in Medical Imaging Reconstruction
Marcus Chen, MD · National Heart, Lung, and Blood Institute, National Institutes of Health
Saturday, July 18
Continental breakfast
Local Patches Meet Global Context: Scalable 3D Diffusion Priors for Image Reconstruction
Jeff Fessler, PhD · University of Michigan
Locally Linear Regions of a Network CT Denoiser
Craig Abbey, PhD · University of California, Santa Barbara
Generative AI and Foundation Models for PET and SPECT
Chi Liu, PhD · Yale University
Deep Artifact Reduction
Marc Kachelriess, PhD · German Cancer Research Center (DKFZ)
Break and Meet the TMI Editor-in-Chief
Ge Wang, PhD · Rensselaer Polytechnic Institute
Recording not planned for publication
New Methods for Super-Resolution and Harmonization in MR Neuroimaging
Jerry Prince, PhD · Johns Hopkins University
Diffusion Models-Based PET Image Reconstruction
Kuang Gong, PhD · University of Florida
Deep Learning & Statistical CT Reconstruction: From Model to Clinical Applications
Wenjing Cao, PhD · United Imaging Healthcare
Deep Learning for 3D Reconstructions from Cryo-Electron Microscopy Data
Kanupriya Pande, PhD · Lawrence Berkeley National Laboratory
Generative Translation Priors: Bayesian Imaging with Cross-Modality Image Translation
Yu Sun, PhD · Johns Hopkins University
Closing remarks
Previous Meetings
- 2025 — Johns Hopkins University Organizer: J. Webster Stayman
- 2023 — Yale University Organizer: Chi Liu
- 2021 — Massachusetts General Hospital Organizer: Quanzheng Li
- 2020 — GE Global Research Organizers: Bruno De Man and Amanda Youmans
- 2017 — Rensselaer Polytechnic Institute Organizers: Ge Wang and Hongming Shan