Segmentation algorithms of subcortical brain structures on MRI : a review

Dolz, J.; Massoptier, L; Vermandel, Maximilien

Document type :

Article dans une revue scientifique

Title :

Segmentation algorithms of subcortical brain structures on MRI : a review

Author(s) :

Dolz, J. [Auteur]
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]
Massoptier, L [Auteur]
Vermandel, Maximilien [Auteur]
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]

Journal title :

Journal of Neuroimage

Pages :

200/212

Publication date :

2014-09-23

HAL domain(s) :

Sciences du Vivant [q-bio]/Cancer

English abstract : [en]

AbstractThis work covers the current state of the art with regard to approaches to segment subcortical brain structures. A huge range of diverse methods have been presented in the literature during the last decade to segment ...
Show more >AbstractThis work covers the current state of the art with regard to approaches to segment subcortical brain structures. A huge range of diverse methods have been presented in the literature during the last decade to segment not only one or a constrained number of structures, but also a complete set of these subcortical regions. Special attention has been paid to atlas based segmentation methods, statistical models and deformable models for this purpose. More recently, the introduction of machine learning techniques, such as artificial neural networks or support vector machines, has helped the researchers to optimize the classification problem. These methods are presented in this work, and their advantages and drawbacks are further discussed. Although these methods have proved to perform well, their use is often limited to those situations where either there are no lesions in the brain or the presence of lesions does not highly vary the brain anatomy. Consequently, the development of segmentation algorithms that can deal with such lesions in the brain and still provide a good performance when segmenting subcortical structures is highly required in practice by some clinical applications, such as radiotherapy or radiosurgery.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

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