250 citations · 531 across the 23 of their papers we have counts for
10 papers · 1 filter
Deep Learning with Mixed Supervision for Brain Tumor Segmentation
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi +1
Most of the current state-of-the-art methods for tumor segmentation are based on machine learning models trained on manually segmented images. This type of training data is particu…
Learning a Probabilistic Model for Diffeomorphic Registration
Julian Krebs, Hervé Delingette, Boris Mailhé +2
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for registration and the analysis of deformations. The latent variable model maps…
Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow
Qiao Zheng, Hervé Delingette, Nicholas Ayache
We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart. An original semi-su…
Alzheimer's Disease Modelling and Staging through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes
Clement Abi Nader, Nicholas Ayache, Philippe Robert +1
Alzheimer's disease (AD) is characterized by complex and largely unknown progression dynamics affecting the brain's morphology. Although the disease evolution spans decades, to dat…
Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease
Luigi Antelmi, Nicholas Ayache, Philippe Robert +1
The joint analysis of biomedical data in Alzheimer's Disease (AD) is important for better clinical diagnosis and to understand the relationship between biomarkers. However, jointly…
3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi +1
We present an efficient deep learning approach for the challenging task of tumor segmentation in multisequence MR images. In recent years, Convolutional Neural Networks (CNN) have…