The objective of our work is the development of a method for the detection of prostate cancer from multiparametric MRI sequences. In this thesis, we detail the main sources of difficulties in the development of such a method as well as ways to overcome them.Chapter 2 deals with the inter-rater variability of volume estimates and zonal...
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June 26, 2023 (v1)PublicationUploaded on: October 11, 2023
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October 4, 2020 (v1)Conference paper
The fusion of probability maps is required when trying to analyse a collection of image labels or probability maps produced by several segmentation algorithms or human raters. The challenge is to weight properly the combination of maps in order to reflect the agreement among raters, the presence of outliers and the spatial uncertainty in the...
Uploaded on: December 4, 2022 -
November 18, 2020 (v1)Conference paper
ObjectifsL'objectif de l'étude est le développement d'un outil de segmentation automatique de l'anatomie zonale prostatique sur la séquence en pondération T2 en IRM, basé sur l'apprentissage profond (réseau de neurones), robuste quelle que soit la variabilité morphologique de la prostate et les caractéristiques techniques des séquences...
Uploaded on: December 4, 2022 -
September 14, 2023 (v1)Journal article
The extraction of consensus segmentations from several binary or probabilistic masks is important to solve various tasks such as the analysis of inter-rater variability or the fusion of several neural network outputs. One of the most widely used methods to obtain such a consensus segmentation is the STAPLE algorithm. In this paper, we first...
Uploaded on: October 11, 2023 -
May 2022 (v1)Journal article
The fusion of probability maps is required when trying to analyse a collection of image labels or probability maps produced by several segmentation algorithms or human raters. The challenge is to weight the combination of maps correctly, in order to reflect the agreement among raters, the presence of outliers and the spatial uncertainty in the...
Uploaded on: December 3, 2022 -
March 14, 2022 (v1)Journal article
Purpose: An accurate zonal segmentation of the prostate is required for prostate cancer management with MRI.Approach:The aim of this work is to present UFNet, a deep learning-based method for automatic zonal segmentation of the prostate from T2-weighted (T2w) MRI. It takes into account the image anisotropy, includes both spatial andchannel-wise...
Uploaded on: December 3, 2022 -
September 18, 2022 (v1)Conference paper
International audience
Uploaded on: December 4, 2022