7 citations · 16 across the 10 of their papers we have counts for
18 papers
Test-Time Adaptation with Shape Moments for Image Segmentation
Mathilde Bateson, Hervé Lombaert, Ismail Ben Ayed
Supervised learning is well-known to fail at generalization under distribution shifts. In typical clinical settings, the source data is inaccessible and the target distribution is…
Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation
Sukesh Adiga, Jose Dolz, Herve Lombaert
Semi-supervised segmentation tackles the scarcity of annotations by leveraging unlabeled data with a small amount of labeled data. A prominent way to utilize the unlabeled data is…
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging
Benoit Anctil-Robitaille, Antoine Théberge, Pierre-Marc Jodoin +3
The physical and clinical constraints surrounding diffusion-weighted imaging (DWI) often limit the spatial resolution of the produced images to voxels up to 8 times larger than tho…
Realistic Image Normalization for Multi-Domain Segmentation
Pierre-Luc Delisle, Benoit Anctil-Robitaille, Christian Desrosiers +1
Image normalization is a building block in medical image analysis. Conventional approaches are customarily utilized on a per-dataset basis. This strategy, however, prevents the cur…
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images
Adrian Galdran, José Dolz, Hadi Chakor +2
Assessing the degree of disease severity in biomedical images is a task similar to standard classification but constrained by an underlying structure in the label space. Such a str…
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
Adrian Galdran, André Anjos, José Dolz +3
The segmentation of the retinal vasculature from eye fundus images represents one of the most fundamental tasks in retinal image analysis. Over recent years, increasingly complex a…