activity
20152025
most citedSemi-supervised few-shot learning for medical image segmentation

61 citations · 97 across the 23 of their papers we have counts for

collaborators
Showing 2018Show all

8 papers · 1 filter

eess.IV2018

Boundary loss for highly unbalanced segmentation

Hoel Kervadec, Jihene Bouchtiba, Christian Desrosiers +3

Widely used loss functions for CNN segmentation, e.g., Dice or cross-entropy, are based on integrals over the segmentation regions. Unfortunately, for highly unbalanced segmentatio…

cs.LG2018

Scalable Laplacian K-modes

Imtiaz Masud Ziko, Eric Granger, Ismail Ben Ayed

We advocate Laplacian K-modes for joint clustering and density mode finding, and propose a concave-convex relaxation of the problem, which yields a parallel algorithm that scales u…

cs.CV2018

IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet

Jose Dolz, Christian Desrosiers, Ismail Ben Ayed

Accurate localization and segmentation of intervertebral disc (IVD) is crucial for the assessment of spine disease diagnosis. Despite the technological advances in medical imaging,…

cs.CV2018

Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses

Jérôme Rony, Luiz G. Hafemann, Luiz S. Oliveira +3

Research on adversarial examples in computer vision tasks has shown that small, often imperceptible changes to an image can induce misclassification, which has security implication…

cs.CV2018

Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities

Jose Dolz, Ismail Ben Ayed, Christian Desrosiers

Delineating infarcted tissue in ischemic stroke lesions is crucial to determine the extend of damage and optimal treatment for this life-threatening condition. However, this proble…

cs.CV2018

Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

Jose Dolz, Xiaopan Xu, Jerome Rony +7

Precise segmentation of bladder walls and tumor regions is an essential step towards non-invasive identification of tumor stage and grade, which is critical for treatment decision…