Computer-aided analysis of prostate multiparametric MR images: an unsupervised fusion-based approach

Betrouni, Nacim; Makni, Nasr; Lakroum, S; Mordon, Serge; Villers, Arnaud; Puech, Pascal

Document type :

Compte-rendu et recension critique d'ouvrage

Title :

Computer-aided analysis of prostate multiparametric MR images: an unsupervised fusion-based approach

Author(s) :

Betrouni, Nacim [Auteur]

Université de Lille, Droit et Santé
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]
Makni, Nasr [Auteur]
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]
Lakroum, S [Auteur]
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]
Mordon, Serge [Auteur]
Université de Lille, Droit et Santé
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]
Villers, Arnaud [Auteur]
Université de Lille, Droit et Santé
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]
Puech, Pascal [Auteur]
Université de Lille, Droit et Santé
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]

Journal title :

International Journal of Computer Assisted Radiology and Surgery

Pages :

01/12

Publisher :

Springer Verlag

Publication date :

2015-01-22

ISSN :

1861-6410

HAL domain(s) :

Sciences du Vivant [q-bio]/Cancer

English abstract : [en]

OBJECTIVE: The aim of this study is to provide an automatic framework for computer-aided analysis of multiparametric magnetic resonance (mp-MR) images of prostate.METHOD: We introduce a novel method for the unsupervised ...
Show more >OBJECTIVE: The aim of this study is to provide an automatic framework for computer-aided analysis of multiparametric magnetic resonance (mp-MR) images of prostate.METHOD: We introduce a novel method for the unsupervised analysis of the images. An evidential C-means classifier was adapted for use with a segmentation scheme to address multisource data and to manage conflicts and redundancy.RESULTS: Experiments were conducted using data from 15 patients. The evaluation protocol consisted in evaluating the method abilities to classify prostate tissues, showing the same behaviour on the mp-MR images, into homogeneous classes. As the actual diagnosis was available, thanks to the correlation with histopathological findings, the assessment focused on the ability to segment cancer foci. The method exhibited global sensitivity and specificity of 70 and 88 %, respectively.CONCLUSION: The preliminary results obtained by these initial experiments showed that the method can be applied in clinical routine practice to help making decision especially for practitioners with limited experience in prostate MRI analysis.Show less >

Language :

Anglais

Popular science :

Non

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