DocumentCode
2939485
Title
Brain lesion detection in MRI with fuzzy and geostatistical models
Author
Pham, Tuan D.
Author_Institution
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
fYear
2010
fDate
Aug. 31 2010-Sept. 4 2010
Firstpage
3150
Lastpage
3153
Abstract
Automated image detection of white matter changes of the brain is essentially helpful in providing a quantitative measure for studying the association of white matter lesions with other types of biomedical data. Such study allows the possibility of several medical hypothesis validations which lead to therapeutic treatment and prevention. This paper presents a new clustering-based segmentation approach for detecting white matter changes in magnetic resonance imaging with particular reference to cognitive decline in the elderly. The proposed method is formulated using the principles of fuzzy c-means algorithm and geostatistics.
Keywords
biomedical MRI; brain; cognition; fuzzy set theory; geriatrics; image segmentation; medical image processing; statistical analysis; MRI; brain lesion detection; clustering-based segmentation; cognition; elderly; fuzzy c-means algorithm; geostatistical models; magnetic resonance imaging; white matter lesions; Biomedical imaging; Computed tomography; Image segmentation; Lesions; Magnetic resonance imaging; Manuals; Senior citizens; Algorithms; Artificial Intelligence; Brain; Brain Neoplasms; Computer Simulation; Data Interpretation, Statistical; Female; Fuzzy Logic; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Models, Biological; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location
Buenos Aires
ISSN
1557-170X
Print_ISBN
978-1-4244-4123-5
Type
conf
DOI
10.1109/IEMBS.2010.5627188
Filename
5627188
Link To Document