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08/22/2023
Non-Redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer
We address the problem of learning Deep Learning Radiomics (DLR) that ar...
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07/10/2023
Weakly-supervised positional contrastive learning: application to cirrhosis classification
Large medical imaging datasets can be cheaply and quickly annotated with...
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02/16/2023
Learning to diagnose cirrhosis from radiological and histological labels with joint self and weakly-supervised pretraining strategies
Identifying cirrhosis is key to correctly assess the health of the liver...
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10/21/2022
Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection
We propose a scalable and data-driven approach to learn shape distributi...
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10/15/2022
CoRe: An Automated Pipeline for The Prediction of Liver Resection Complexity from Preoperative CT Scans
Surgical resections are the most prevalent curative treatment for primar...
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09/07/2020
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications
Statistical shape modeling (SSM) is widely used in biology and medicine ...
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03/27/2018
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms
We propose a method to learn a distribution of shape trajectories from l...
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11/23/2017
Parallel transport in shape analysis: a scalable numerical scheme
The analysis of manifold-valued data requires efficient tools from Riema...
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11/23/2017
