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

Rahima Zaouche Ahrour Belaidi Soraya Aloui Basel Solaiman 1 Ahcène Bounceur 2, 3 Douraied Ben Salem Seddik Sid Ahmed 4 Souheil Tliba 
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
Abstract : 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.
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Conference papers
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Contributor : Ahcène Bounceur Connect in order to contact the contributor
Submitted on : Sunday, March 27, 2016 - 5:03:15 PM
Last modification on : Monday, June 27, 2022 - 3:06:51 AM


  • HAL Id : hal-01294147, version 1


Rahima Zaouche, Ahrour Belaidi, Soraya Aloui, Basel Solaiman, Ahcène Bounceur, et al.. Segmentation of low-grade gliomas in MRI : Phase based method. International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016), Mar 2016, Monastir, Tunisia. ⟨hal-01294147⟩



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