Workshop on Multimodal AI for Healthcare

MR-zero: Discovering new MR sequences using Artificial Intelligence, Peter Dawood (FAU)

Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations, Veronika Spieker (TUM)

Resource-efficient Medical Image Analysis with Self-adapting Forward-Forward Networks, Johanna Müller (FAU)

Diffusion-based Interpolation for Cardiac MRI Supersampling, Niklas Bubeck (TUM)

A Novel Device Tracker in X-ray Using Supplementary-cue driven  Spatio-Temporal Self-Supervised Features, Saahil Islam (FAU)

Tools for vascular biomarker extraction from retinal images for multimodal disease predictions, Linus Kreitner (TUM)

TBD, Annette Schwarz (FAU)

RaDialog: Large Vision-Language Models for X-Ray Reporting and Dialog-Driven Assistance, Chantal Pellegrini (TUM)

Multi-Agent Guideline-Driven Diagnostic Assistance David Bani-Harouni (FAU)

Vision and Multimodal Learning in Medical Imaging, Cosmin Bercea (TUM)

Differentiable score-based likelihoods: Learning CT motion compensation from clean images, Mareike Thies (FAU)

Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images, Yundi Zhang (TUM)

Image Distillation for Safe Data Sharing in Histopathology, Zhe Li (FAU)

Integration of variant annotations using deep set networks boosts rare variant association testing, Eva Holtkamp (TUM)

Uncertainty-Aware Vision Transformers for Medical Image Analysis, Franciskus Xaverius Erick (FAU)

Functional gene embeddings improve rare variant polygenic risk scores, Shubhankar Londhe(TUM)

A Feature Weighting-Assisted Approach for Cancer Subtypes Identification by Integrating Multi-omics Data, Sushmita Paul (FAU)