DocumentCode
636299
Title
Unsupervised segmentation of brain regions with similar microstructural properties: Application to alcoholism
Author
Cosa, Alejandro ; Canals, Santiago ; Valles-Lluch, A. ; Moratal, David
Author_Institution
Inst. de Neurociencias, Univ. Miguel Hernandez de Elche, San Juan, Spain
fYear
2013
fDate
3-7 July 2013
Firstpage
1053
Lastpage
1056
Abstract
In this work, a novel brain MRI segmentation approach evaluates microstructural differences between groups. Going further from the traditional segmentation of brain tissues (white matter -WM-, gray matter -GM- and cerebrospinal fluid -CSF- or a mixture of them), a new way to classify brain areas is proposed using their microstructural MR properties. Eight rats were studied using the proposed methodology identifying regions which present microstructural differences as a consequence on one month of hard alcohol consumption. Differences in relaxation times of the tissues have been found in different brain regions (p<;0.05). Furthermore, these changes allowed the automatic classification of the animals based on their drinking history (hit rate of 93.75 % of the cases).
Keywords
biological tissues; biomedical MRI; brain; image classification; image segmentation; medical disorders; medical image processing; neurophysiology; alcoholism application; automatic classification; brain MRI segmentation approach; brain areas; brain regions; brain tissues; hard alcohol consumption; microstructural MR properties; microstructural differences; traditional segmentation; unsupervised segmentation; Alcoholic beverages; Alcoholism; Animals; Brain modeling; Covariance matrices; Image segmentation; Magnetic resonance imaging; Alcoholism; Animals; Bayes Theorem; Brain; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Rats;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location
Osaka
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2013.6609685
Filename
6609685
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