8 papers
A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI
Eryn Libert-Scott, Emma A. M. Stanley, Vibujithan Vigneshwaran +3
Causally linking disease-related factors to image-derived biomarkers provides a powerful pathway to understanding disease mechanisms. Despite growing interest in applying causal ar…
Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge
Asbjørn Munk, Stefano Cerri, Vardan Nersesjan +81
Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are prohibitively costly to obt…
From Redaction to Restoration: Deep Learning for Medical Image Anonymization and Reconstruction
Adrienne Kline, Abhijit Gaonkar, Daniel Pittman +2
Removing patient-specific information from medical images is crucial to enable sharing and open science without compromising patient identities. However, many methods currently use…
CRAwDAD: Causal Reasoning Augmentation with Dual-Agent Debate
Finn G. Vamosi, Nils D. Forkert
When people reason about cause and effect, they often consider many competing "what if" scenarios before deciding which explanation fits best. Analogously, advanced language models…
Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge
Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47
The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…
Semi-disentangled spatiotemporal implicit neural representations of longitudinal neuroimaging data for trajectory classification
Agampreet Aulakh, Nils D. Forkert, Matthias Wilms
The human brain undergoes dynamic, potentially pathology-driven, structural changes throughout a lifespan. Longitudinal Magnetic Resonance Imaging (MRI) and other neuroimaging data…