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7 papers · 2 filters
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…
Generalizable multi-task, multi-domain deep segmentation of sparse pediatric imaging datasets via multi-scale contrastive regularization and multi-joint anatomical priors
Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons +2
Clinical diagnosis of the pediatric musculoskeletal system relies on the analysis of medical imaging examinations. In the medical image processing pipeline, semantic segmentation u…
Perfusion imaging in deep prostate cancer detection from mp-MRI: can we take advantage of it?
Audrey Duran, Gaspard Dussert, Carole Lartizien
To our knowledge, all deep computer-aided detection and diagnosis (CAD) systems for prostate cancer (PCa) detection consider bi-parametric magnetic resonance imaging (bp-MRI) only,…
Learning to segment prostate cancer by aggressiveness from scribbles in bi-parametric MRI
Audrey Duran, Gaspard Dussert, Carole Lartizien
In this work, we propose a deep U-Net based model to tackle the challenging task of prostate cancer segmentation by aggressiveness in MRI based on weak scribble annotations. This m…
Multi-Channel Convolutional Analysis Operator Learning for Dual-Energy CT Reconstruction
Alessandro Perelli, Suxer Alfonso Garcia, Alexandre Bousse +3
Objective. Dual-energy computed tomography (DECT) has the potential to improve contrast, reduce artifacts and the ability to perform material decomposition in advanced imaging appl…
Anatomically Parameterized Statistical Shape Model: Explaining Morphometry through Statistical Learning
Arnaud Boutillon, Asma Salhi, Valérie Burdin +1
Statistical shape models (SSMs) are a popular tool to conduct morphological analysis of anatomical structures which is a crucial step in clinical practices. However, shape represen…