Title :

Supervised machine learning based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context

Author(s) :

Dolz, J. [Auteur]
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]
Laprie, Anne [Auteur]
Imagerie cérébrale et handicaps neurologiques [ICHN]
Ken, Soléakhéna [Auteur]
Imagerie cérébrale et handicaps neurologiques [ICHN]
Leroy, Henri-Arthur [Auteur]
Noyaux gris centraux
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]
Reyns, Nicolas [Auteur]
Noyaux gris centraux
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]
Massoptier, Laurent [Auteur]
Noyaux gris centraux
Vermandel, Maximilien [Auteur]
Noyaux gris centraux
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]

Journal title :

International Journal of Computer Assisted Radiology and Surgery

Pages :

1/16

Publisher :

Springer Verlag

Publication date :

2015-07-24

ISSN :

1861-6410

HAL domain(s) :

Sciences du Vivant [q-bio]/Cancer

English abstract : [en]

Purpose To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk (OARs) is required. This task is still manually performed, which is time-consuming and prone ...
Show more >Purpose To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk (OARs) is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address these issues, and as alternative to atlas-based segmentation methods, machine learning techniques, such as support vector machines (SVM), have been recently presented to segment subcortical structures on magnetic resonance images (MRI).Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189

Source :

Harvested from HAL