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

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.
Type de document :
Communication dans un congrès
International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016), Mar 2016, Monastir, Tunisia. International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016)
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http://hal.univ-brest.fr/hal-01294147
Contributeur : Ahcène Bounceur <>
Soumis le : dimanche 27 mars 2016 - 17:03:15
Dernière modification le : vendredi 23 février 2018 - 15:22:28

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  • HAL Id : hal-01294147, version 1

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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. International Conference on Advanced Technologies for Signal and Image Processing (ATSIP’2016). 〈hal-01294147〉

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