DocumentCode
2465251
Title
Partial volume estimation and the fuzzy C-means algorithm [brain MRI application]
Author
Pham, Dzung L. ; Prince, Jerry I.
Author_Institution
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
fYear
1998
fDate
4-7 Oct 1998
Firstpage
819
Abstract
Partial volume averaging (PVA) is present in nearly all practical imaging situations, medical imaging in particular. One method that has been used to account for the effects of PVA is the fuzzy c-means algorithm (FCM). The authors propose a new method for estimating the partial volume coefficient of each class at each voxel in a given image using a Bayesian statistical model. A prior probability on the partial volume coefficients is used to reject how most voxels in the image are expected to be pure. The authors then show that the results obtained by this method are quite similar and in some cases equivalent to results obtained using FCM. Both algorithms are demonstrated on a magnetic resonance image of the brain
Keywords
Bayes methods; biomedical MRI; brain; medical image processing; modelling; Bayesian statistical model; a prior probability; brain MRI; fuzzy c-means algorithm; magnetic resonance imaging; medical diagnostic imaging; voxel; Anatomical structure; Bayesian methods; Biomedical imaging; Cognition; Gerontology; Image resolution; Image segmentation; Magnetic noise; Magnetic resonance; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location
Chicago, IL
Print_ISBN
0-8186-8821-1
Type
conf
DOI
10.1109/ICIP.1998.999071
Filename
999071
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