103 citations · 109 across the 4 of their papers we have counts for
9 papers
ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans
Audrey Duran, Gaspard Dussert, Olivier Rouvière +3
Multiparametric magnetic resonance imaging (mp-MRI) has shown excellent results in the detection of prostate cancer (PCa). However, characterizing prostate lesions aggressiveness i…
Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients
Verónica Muñoz-Ramírez, Nicolas Pinon, Florence Forbes +2
Although neural networks have proven very successful in a number of medical image analysis applications, their use remains difficult when targeting subtle tasks such as the identif…
LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography
Sarah Leclerc, Erik Smistad, Andreas Østvik +9
Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semi-automatically in clinical routine,…
Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography
Sarah Leclerc, Erik Smistad, João Pedrosa +11
Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has be…
Deep Learning Segmentation in 2D echocardiography using the CAMUS dataset : Automatic Assessment of the Anatomical Shape Validity
Sarah Leclerc, Erik Smistad, Andreas Østvik +9
We recently published a deep learning study on the potential of encoder-decoder networks for the segmentation of the 2D CAMUS ultrasound dataset. We propose in this abstract an ext…
Feature Selection for Unsupervised Domain Adaptation using Optimal Transport
Léo Gautheron, Ievgen Redko, Carole Lartizien
In this paper, we propose a new feature selection method for unsupervised domain adaptation based on the emerging optimal transportation theory. We build upon a recent theoretical…