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Keywords
(10)
Biomedical Imaging
Brain Tissue
Fuzzy C Mean
Image Segmentation
Magnetic Resonance Image
Objective Function
Singular Value
Spatial Information
Standard Deviation
Multi Dimensional
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Separation of brain tissues in MRI based on multi-dimensional FCM and spatial information
Separation of brain tissues in MRI based on multi-dimensional FCM and spatial information,10.1109/FSKD.2011.6019589,Jamal Ghasemi,Reza Ghaderi,Mohamad
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Separation of brain tissues in MRI based on multi-dimensional FCM and spatial information
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Jamal Ghasemi
,
Reza Ghaderi
,
Mohamad Reza Karami Mollaei
,
Ali Hojjatoleslami
Due to intensity non-uniformity (INU) and noise brain
magnetic resonance image
(MRI) segmentation is a complicated concern. Many methods have been presented to overcome brain MRI segmentation. Among these methods, using fuzzy c-means (FCM) is introduced as an effective strategy.
Spatial information
cannot be considered at a standard FCM. Therefore, many methods have been presented to optimize standard FCM with optimization of objective function. In this research work, a novel method has been proposed for brain MRI segmentation (BMS) based on multi-dimensional standard FCM. In this technique, different features of neighboring pixels such as mean,
standard deviation
and
singular value
in combination with pixel intensity has been used for typical pixel segmentation. The results have been evaluated against manual segmentation on a publicly available dataset.
Conference:
Fuzzy Systems and Knowledge Discovery
, 2011
DOI:
10.1109/FSKD.2011.6019589
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