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Proceedings Paper

A boosting approach for prostate cancer detection using multi-parametric MRI
Author(s): Guillaume Lemaitre; Joan Massich; Robert Martí; Jordi Freixenet; Joan C. Vilanova; Paul M. Walker; Désiré Sidibé; Fabrice Mériaudeau
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Paper Abstract

Prostate cancer has been reported as the second most frequently diagnosed men cancers in the world. In the last decades, new imaging techniques based on MRI have been developed in order to improve the diagnosis task of radiologists. In practise, diagnosis can be affected by multiple factors reducing the chance to detect potential lesions. Computer-aided detection and computer-aided diagnosis have been designed to answer to these needs and provide help to radiologists in their daily duties. In this study, we proposed an automatic method to detect prostate cancer from a per voxel manner using 3T multi-parametric Magnetic Resonance Imaging (MRI) and a gradient boosting classifier. The best performances are obtained using all multi-parametric information as well as zonal information. The sensitivity and specificity obtained are 94:7% and 93:0%, respectively and an Area Under Curve (AUC) of 0:968.

Paper Details

Date Published: 30 April 2015
PDF: 7 pages
Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 95340A (30 April 2015); doi: 10.1117/12.2182772
Show Author Affiliations
Guillaume Lemaitre, Le2i, CNRS, Univ. de Bourgogne (France)
Univ. de Girona (Spain)
Joan Massich, Le2i, CNRS, Univ. de Bourgogne (France)
Robert Martí, Univ. de Girona (Spain)
Jordi Freixenet, Univ. de Girona (Spain)
Joan C. Vilanova, Clínica Girona (Spain)
Paul M. Walker, Le2i, CNRS, Univ. de Bourgogne (France)
Désiré Sidibé, Le2i, CNRS, Univ. de Bourgogne (France)
Fabrice Mériaudeau, Le2i, CNRS, Univ. de Bourgogne (France)


Published in SPIE Proceedings Vol. 9534:
Twelfth International Conference on Quality Control by Artificial Vision 2015
Fabrice Meriaudeau; Olivier Aubreton, Editor(s)

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