1. Segmentation of low-grade gliomas in MRI : Phase based method
- Author
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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 ), and Bounceur, Ahcène
- Subjects
medicine.medical_specialty ,Low-grade glioma ,Fluid-attenuated inversion recovery ,Surgical planning ,030218 nuclear medicine & medical imaging ,local phase information ,03 medical and health sciences ,0302 clinical medicine ,Glioma ,medicine ,Medical physics ,Segmentation ,monogenic signal ,MRI segmentation ,medicine.diagnostic_test ,business.industry ,Magnetic resonance imaging ,Image segmentation ,medicine.disease ,[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV] ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,Dynamic contrast-enhanced MRI ,Radiology ,Brain tumor segmentation ,business ,030217 neurology & neurosurgery - 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.
- Published
- 2016