Title :

Gland and zonal segmentation of prostate on t2w mr images

Author(s) :

Chilali, O. [Auteur]
Puech, Philippe [Auteur]
Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189
Lakroum, Said [Auteur]
Diaf, M. [Auteur]
Mordon, Serge [Auteur]
Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189
Betrouni, Nacim [Auteur]
Troubles cognitifs dégénératifs et vasculaires - U1171

Journal title :

Journal of digital imaging

Abbreviated title :

J. Digit. Imaging

Volume number :

29

Pages :

730-736

Publication date :

2016-12-01

ISSN :

0897-1889

English keyword(s) :

Zones
Prostate
Atlas
Segmentation
MRT2W images
Mesh:Magnetic Resonance Imaging/methods*
Mesh:Male
Mesh:Algorithms*
Mesh:Databases
Mesh:Factual
Mesh:Humans
Mesh:Prostate/diagnostic imaging*
Mesh:Prostatic Neoplasms/diagnostic imaging*

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

For many years, prostate segmentation on MR images concerned only the extraction of the entire gland. Currently, in the focal treatment era, there is a continuously increasing need for the separation of the different parts ...
Show more >For many years, prostate segmentation on MR images concerned only the extraction of the entire gland. Currently, in the focal treatment era, there is a continuously increasing need for the separation of the different parts of the organ. In this paper, we propose an automatic segmentation method based on the use of T2W images and atlas images to segment the prostate and to isolate the peripheral and transition zones. The algorithm consists of two stages. First, the target image is registered with each zonal atlas image then the segmentation is obtained by the application of an evidential C-Means clustering. The method was evaluated on a representative and multi-centric image base and yielded mean Dice accuracy values of 0.81, 0.70, and 0.62 for the prostate, the transition zone, and peripheral zone, respectively.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

CHU Lille
CNRS
Inserm
Université de Lille

Collections :

• Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189
• Troubles cognitifs dégénératifs et vasculaires - U1171

Submission date :

2019-11-27T13:04:04Z