DocumentCode
575114
Title
Unsupervised abdomen CT image segmentation using variable weight MRF in spatial and wavelet domain
Author
Ma, Zhiyuan ; Jiang, Huiyan ; Yang, Benqiang ; Zhang, Libo
Author_Institution
Software Coll., Northeastern Univ., Shenyang, China
fYear
2011
fDate
Nov. 29 2011-Dec. 1 2011
Firstpage
915
Lastpage
921
Abstract
Aiming at the segmentation of liver image with fuzzy edge, a new algorithm based on Markov Random Field in spatial and wavelet domains is proposed. Firstly, a lifting wavelet transform is adopted to represent an original image in different resolutions; Secondly, attain the low frequency subimage and execute an initial segmentation and a multi-level segmentation; Lastly, the spatial domain transform is applied on the segmentation result of the wavelet domain to revise the segmentation results and to get an accurate outcome. The algorithms of the initial and multi-level segmentation in wavelet domain are K-means improved by SAPSO and MAP/ICM. Experimental results show that the proposed algorithm has a good robustness.
Keywords
Markov processes; computerised tomography; fuzzy set theory; image segmentation; medical image processing; wavelet transforms; K-means; MAP-ICM; Markov random field; SAPSO; fuzzy edge; lifting wavelet transform; liver image segmentation; multilevel segmentation; spatial domain transform; unsupervised abdomen CT image segmentation; variable weight MRF; wavelet domain; Computed tomography; Equations; Image segmentation; Mathematical model; Wavelet domain; Wavelet transforms; Abdomen CT imag; ICM; Image segmentation; MAP; Markov Random Field; Simulated Annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
Conference_Location
Seogwipo
Print_ISBN
978-1-4577-0472-7
Type
conf
Filename
6316750
Link To Document