Multi‐eXpert fusion: An ensemble learning framework to segment 3D TRUS prostate images
Author:
Affiliation:
1. Univ. Grenoble Alpes CNRS CHU Grenoble Alpes Grenoble INP TIMC‐IMAG Grenoble France
Funder
Région Auvergne-Rhône-Alpes
Agence Nationale de la Recherche
Publisher
Wiley
Subject
General Medicine
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15679
Reference20 articles.
1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries
2. Intra- and inter-observer variability and reliability of prostate volume measurement via two-dimensional and three-dimensional ultrasound imaging
3. YangX FeiB.3D prostate segmentation of ultrasound images combining longitudinal image registration and machine learning. InMedical Imaging 2012: Image‐Guided Procedures Robotic Interventions and Modeling.2012;8316:83162O.
4. YangX RossiPJ JaniAB MaoH CurranWJ LiuT.3D transrectal ultrasound (TRUS) prostate segmentation based on optimal feature learning framework. InMedical Imaging 2016: Image Processing.2016.
5. Accurate and Robust Segmentation of the Clinical Target Volume for Prostate Brachytherapy
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