6 citations · 7 across the 5 of their papers we have counts for
5 papers
Disease Progression and Subtype Modeling for Combined Discrete and Continuous Input Data
Sterre de Jonge, Elisabeth J. Vinke, Meike W. Vernooij +3
Disease progression modeling provides a robust framework to identify long-term disease trajectories from short-term biomarker data. It is a valuable tool to gain a deeper understan…
AI-based association analysis for medical imaging using latent-space geometric confounder correction
Xianjing Liu, Bo Li, Meike W. Vernooij +3
This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves…
Deep learning-based group-wise registration for longitudinal MRI analysis in glioma
Claudia Chinea Hammecher, Karin van Garderen, Marion Smits +8
Glioma growth may be quantified with longitudinal image registration. However, the large mass-effects and tissue changes across images pose an added challenge. Here, we propose a l…
Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021
Carole H. Sudre, Kimberlin Van Wijnen, Florian Dubost +46
Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and…
Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
Xianjing Liu, Bo Li, Esther Bron +3
Confounding bias is a crucial problem when applying machine learning to practice, especially in clinical practice. We consider the problem of learning representations independent t…