Segmentation of brain tissue based on connected component labeling and mathematic morphology
In order to realize more accurate and efficient segmentation of the Visible Human dataset, an indirect algorithm based on connected component labeling and mathematic morphology was proposed for brain tissue segmentation in this paper. Initially, the region of nonbrain tissue was roughly distinguished through connected component labeling. Then its edge was refined by means of dilation and erosion to complete tbe segmentation of nonbrain tissue. Finally, extraction of brain tissue was realized by eliminating the segmented nonbrain tissue from the original image. The experimental results show that the proposed algorithm can lead to satisfactory segmentation of brain tissue.
brain tissue mathematic morphology connected component labeling cryosection images
Min Li Xiaolin Zheng Xiaoping Wan Hongyan Luo Shaoxiang Zhang Liwen Tan
College of Bioengineering,Chongqing University,Chongqing, China Department of Anatomy,Third Military Medical University,Chongqing, China
国际会议
上海
英文
481-484
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）