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Segmentation of low-grade gliomas based on the growing region and level sets techniques
被引:0
作者:
Rahima, Zaouche
[1
]
Ahror, Belaid
[1
]
Basel, Solaiman
[2
]
Douraied, Ben Salem
[3
,4
]
Souhil, Tliba
[5
,6
]
机构:
[1] Univ Abderrahmane Mira, LIMED Lab, Bejaia 06000, Algeria
[2] IMT Atlantique, Image & Informat Proc Dept, F-29238 Brest, France
[3] INSERM, LaTIM, UMR 1101, 5 Ave Foch, F-29200 Brest, France
[4] CHRU Cavale blanche, Neuroradiol Dept, Blvd Tanguy Prigent, F-29609 Brest, France
[5] Univ Abderrahmane Mira, Neurosurg Dept, Res Lab, Bejaia 06000, Algeria
[6] Univ Abderrahmane Mira, Univ Hosp Ctr, Biol Engn Cancers, Bejaia 06000, Algeria
来源:
2018 4TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP)
|
2018年
关键词:
Segmentation;
low-grade gliomas;
level set;
growing region;
D O I:
暂无
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
In this paper, we propose a novel semi-automatic segmentation method based on the local image properties. Its originality is twofold, the first stands on the intensity invariant of phase-local information for the purpose of low-grade gliomas segmentation in MR images. In a second time, a level set method driven is combined to growing region so as to improve tumor detection. Experiments were conducted on a set of medical images. A comparison between the obtained results and the manual segmentation collected from experts is performed. The preliminary results are interesting and encouraging.
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页数:5
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