标题:Edge multi-scale markov random field model based medical image segmentation in wavelet domain
作者:Tang, Wenjing ;Zhang, Caiming ;Zou, Hailin
作者机构:[Tang, Wenjing ;Zhang, Caiming ] School of Computer Science and Technology, Shandong University, Jinan, China;[Tang, Wenjing ;Zou, Hailin ] School of 更多
会议名称:9th International Conference on Intelligent Computing, ICIC 2013
会议日期:28 July 2013 through 31 July 2013
来源:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
出版年:2013
卷:7996 LNAI
页码:56-63
DOI:10.1007/978-3-642-39482-9_7
关键词:edge; medical image segmentation; MRF; wavelet
摘要:The segmentation algorithms based on MRF often exist edge block effect, and have low operation efficiency by modeling the whole image. To solve the problems the image segmentation algorithm using edge multiscale domain hierarchical Markov model is presented. It views an edge as an observable data series, the image characteristic field is built on a series of edge extracted by wavelet transform, and the label field MRF model based on the edge is established to integrate the scale interaction in the model, then the image segmentation is obtained. The test images and medical images are experimented, and the results show that compared with the WMSRF algorithm, the proposed algorithm can not only distinguish effectively different regions, but also retain the edge information very well, and improve the efficiency. Both the visual effects and evaluation parameters illustrate the effectiveness of the proposed algorithm. © 2013 Springer-Verlag.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883154090&doi=10.1007%2f978-3-642-39482-9_7&partnerID=40&md5=4048e472ca7ac6b05dde95e295686468
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