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Segmentation of low-grade gliomas in MRI : Phase based method

Authors :
S. Sid-Ahmed
R. Zaouche
D. Ben Salem
Basel Solaiman
S. Aloui
S. Tliba
A. Bounceur
Ahror Belaid
Département Image et Traitement Information (ITI)
Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT)
Lab-STICC_UBO_CACS_MOCS
Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC)
École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM)
Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM)
Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)
Université de Brest (UBO)
Service de neurochirurgie [Brest]
Hôpital de la Cavale Blanche - CHRU Brest (CHU - BREST )
Bounceur, Ahcène
Source :
International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016), International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016), Mar 2016, Monastir, Tunisia, ATSIP
Publication Year :
2016
Publisher :
HAL CCSD, 2016.

Abstract

International audience; Segmentation of gliomas in magnetic resonance imaging (MRI) images is a crucial task for early tumor diagnosis and surgical planning. Although many methods for brain tumor segmentation exist, the improvement of this process is still difficult. Indeed, MRI images show complex characteristics and the different tumor tissues are difficult to distinguish from the normal brain tissues; especially the low-grade glioma (LGG), distinguished by their infiltrating character. In fact, it is difficult to extract the tumor from the surrounding healthy parenchyma tissue without any risk of neurological functional sequelae. The purpose of this paper is to provide an overview about a new MRI brain tumor segmentation method based on the local phase information. We applied the proposed method on a set of selected images (Flair, T1 and T1c). Those images were from patients with low-grade glioma. The preliminary results obtained seem to be interesting.

Details

Language :
English
Database :
OpenAIRE
Journal :
International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016), International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016), Mar 2016, Monastir, Tunisia, ATSIP
Accession number :
edsair.doi.dedup.....d9bbe35c3c751e0de86e488300f6aec9