Anatomical structure segmentation in MRI brain images

A standard segmentation problem within Magnetic Resonance Imaging (MRI) is the task of labelling voxels according to their tissue type that are White Matter (WM), Gray Matter (GM), and Cerebrospinal fluid (CSF).Image segmentation provides volumetric quantification of cortical atrophy and thus helps...

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Bibliographic Details
Published in2011 International Conference on Emerging Trends in Electrical and Computer Technology pp. 786 - 791
Main Authors Lakshmi, G Geethu, Suruliandi, A
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2011
Subjects
Alzheimer's disease
Brain Extraction tool
Brain Segmentation
Clustering algorithms
Image segmentation
K-Means clustering
Magnetic resonance imaging
Monitoring
Morphological skull stripping
PSNR
Skull
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Summary:A standard segmentation problem within Magnetic Resonance Imaging (MRI) is the task of labelling voxels according to their tissue type that are White Matter (WM), Gray Matter (GM), and Cerebrospinal fluid (CSF).Image segmentation provides volumetric quantification of cortical atrophy and thus helps in the diagnosis of degenerative diseases such as Epilepsy, Schizophrenia, Alzheimer's disease, Dementia and Hydrocephalus. This work deals with comparison of segmentation results by applying K-Means algorithm after morphological skull stripping and also by using the Brain Extraction Tool(BET) for skull stripping. The results are compared using the parameters such as Mean Square Error(MSE), Peak Signal to Noise Ratio(PSNR) and percentage of area segmented.
ISBN:1424479231
9781424479238
DOI:10.1109/ICETECT.2011.5760225