Your browser doesn't support javascript.
loading
Usefulness of Collaborative Work in the Evaluation of Prostate Cancer from MRI.
Mata, Christian; Walker, Paul; Oliver, Arnau; Martí, Joan; Lalande, Alain.
Afiliação
  • Mata C; Pediatric Computational Imaging Research Group, Hospital Sant Joan de Déu, 08950 Esplugues de Llobregat, Spain.
  • Walker P; Research Centre for Biomedical Engineering (CREB), Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain.
  • Oliver A; ImViA Laboratory, Université de Bourgogne Franche-Comté, 64 Rue de Sully, 21000 Dijon, France.
  • Martí J; Institute of Computer Vision and Robotics, University of Girona, Campus Montilivi, Ed. P-IV, 17003 Girona, Spain.
  • Lalande A; Institute of Computer Vision and Robotics, University of Girona, Campus Montilivi, Ed. P-IV, 17003 Girona, Spain.
Clin Pract ; 12(3): 350-362, 2022 May 20.
Article em En | MEDLINE | ID: mdl-35645317
ABSTRACT
The aim of this study is to show the usefulness of collaborative work in the evaluation of prostate cancer from T2-weighted MRI using a dedicated software tool. The variability of annotations on images of the prostate gland (central and peripheral zones as well as tumour) by two independent experts was firstly evaluated, and secondly compared with a consensus between these two experts. Using a prostate MRI database, experts drew regions of interest (ROIs) corresponding to healthy prostate (peripheral and central zones) and cancer. One of the experts then drew the ROI with knowledge of the other expert's ROI. The surface area of each ROI was used to measure the Hausdorff distance and the Dice coefficient was measured from the respective contours. They were evaluated between the different experiments, taking the annotations of the second expert as the reference. The results showed that the significant differences between the two experts disappeared with collaborative work. To conclude, this study shows that collaborative work with a dedicated tool allows consensus between expertise in the evaluation of prostate cancer from T2-weighted MRI.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article