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  • 标题:A New Parallel Segmentation Algorithm for Medical Image
  • 本地全文:下载
  • 作者:Sun Yongqian ; Xi Liang
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:2
  • 页码:139-146
  • DOI:10.14257/ijsip.2015.8.2.14
  • 出版社:SERSC
  • 摘要:In medical Image analysis, the parallel segmentation is the core technology. As one of the classical methods, regional growth algorithms have some problems: it is hard to confirm the feed points automatically. To solve this defect, a new parallel segmentation algorithm with regional growth and support vector machine (SVM) is proposed. SVMs have a good result in segmentation (classification) but a non-ideal convergence rate which is the advantage of regional growth method. So that, combining them and the idea of the algorithm is: classify by SVM to search the seed points, segment by regional growth method. A curvature flow filter is also used in this algorithm to reduce the noise. The experiments are performed on a parallel environment based on torque. The results show that the algorithm is faster than conventional algorithms and the results are better
  • 关键词:CT Image; Parallel Segmentation; Regional Growth; Support Vector ; Machine
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