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
Link To Document :
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