DocumentCode
301233
Title
Application of the cluster approximation for the simultaneous restoration and segmentation of tomographic images
Author
Wu, Chi-h Sin ; Doerschuk, Peter C.
Author_Institution
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Volume
2
fYear
1995
fDate
23-26 Oct 1995
Firstpage
449
Abstract
We describe a Bayesian restoration and segmentation algorithm based on a pixel-line Markov random field and using an efficient approximation based on locality of interactions. A medical tomography example is given
Keywords
Bayes methods; Markov processes; approximation theory; computerised tomography; edge detection; image restoration; image segmentation; medical image processing; random processes; Bayesian restoration algorithm; Bayesian segmentation algorithm; approximation; cluster approximation; image restoration; image segmentation; interactions locality; medical tomography; pixel-line Markov random field; tomographic images; Additive noise; Bayesian methods; Biomedical imaging; Costs; Image restoration; Image segmentation; Internet; Markov random fields; Pixel; Tomography;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1995. Proceedings., International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-8186-7310-9
Type
conf
DOI
10.1109/ICIP.1995.537512
Filename
537512
Link To Document