NDLI: Brain MR image tumor segmentation with ventricular deformation

Content Provider	IEEE Xplore Digital Library
Author	Kai Xiao Hassanien, A.E. Yan Sun Ng, E.K.K.
Copyright Year	2011
Description	Author affiliation: School of Software, Shanghai Jiao Tong University, China (Kai Xiao; Yan Sun) \|\| Information Technology Department, Cairo University, Egypt (Hassanien, A.E.) \|\| Dept of Sci and Eng, Universiti Tunku Abdul Rahman, Kampar, Malaysia (Ng, E.K.K.)
Abstract	This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is quantified and utilized. With the proposed feature extraction component, lateral ventricular deformation is transformed into an additional feature for brain tumor segmentation. Some comparative experiments using both supervised and unsupervised pattern recognition segmentation methods show the improved tumor segmentation accuracy in some image cases.
Starting Page	213
Ending Page	217
File Size	366792
Page Count	5
File Format	PDF
ISBN	9781457714795
e-ISBN	9781457714818
DOI	10.1109/ICCP.2011.6047871
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-25
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape MRI brain tumor shape analysis MR image Image segmentation Sensitivity Magnetic resonance imaging feature Feature extraction segmentation deformation lateral ventricles medical image analysis Tumors Biomedical imaging
Content Type	Text
Resource Type	Article

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