4 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…
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…
MACAW: A Causal Generative Model for Medical Imaging
Vibujithan Vigneshwaran, Erik Ohara, Matthias Wilms +1
Although deep learning techniques show promising results for many neuroimaging tasks in research settings, they have not yet found widespread use in clinical scenarios. One of the…