527 citations · 2.3k across the 108 of their papers we have counts for
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Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images
Bach Ngoc Kim, Jose Dolz, Pierre-Marc Jodoin +1
This paper presents a client/server privacy-preserving network in the context of multicentric medical image analysis. Our approach is based on adversarial learning which encodes im…
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey
Jérôme Rony, Soufiane Belharbi, Jose Dolz +3
Using deep learning models to diagnose cancer from histology data presents several challenges. Cancer grading and localization of regions of interest (ROIs) in these images normall…
Revisiting CycleGAN for semi-supervised segmentation
Arnab Kumar Mondal, Aniket Agarwal, Jose Dolz +1
In this work, we study the problem of training deep networks for semantic image segmentation using only a fraction of annotated images, which may significantly reduce human annotat…
Discretely-constrained deep network for weakly supervised segmentation
Jizong Peng, Hoel Kervadec, Jose Dolz +3
An efficient strategy for weakly-supervised segmentation is to impose constraints or regularization priors on target regions. Recent efforts have focused on incorporating such cons…
Constrained domain adaptation for Image segmentation
Mathilde Bateson, Jose Dolz, Hoel Kervadec +2
We propose to adapt segmentation networks with a constrained formulation, which embeds domain-invariant prior knowledge about the segmentation regions. Such knowledge may take the…
Min-max Entropy for Weakly Supervised Pointwise Localization
Soufiane Belharbi, Jérôme Rony, Jose Dolz +3
Pointwise localization allows more precise localization and accurate interpretability, compared to bounding box, in applications where objects are highly unstructured such as in me…