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Proceedings Paper

Medical image segmentation based on SLIC superpixels model
Author(s): Xiang-ting Chen; Fan Zhang; Ruo-ya Zhang
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Paper Abstract

Medical imaging has been widely used in clinical practice. It is an important basis for medical experts to diagnose the disease. However, medical images have many unstable factors such as complex imaging mechanism, the target displacement will cause constructed defect and the partial volume effect will lead to error and equipment wear, which increases the complexity of subsequent image processing greatly. The segmentation algorithm which based on SLIC (Simple Linear Iterative Clustering, SLIC) superpixels is used to eliminate the influence of constructed defect and noise by means of the feature similarity in the preprocessing stage. At the same time, excellent clustering effect can reduce the complexity of the algorithm extremely, which provides an effective basis for the rapid diagnosis of experts.

Paper Details

Date Published: 5 January 2017
PDF: 8 pages
Proc. SPIE 10245, International Conference on Innovative Optical Health Science, 1024502 (5 January 2017); doi: 10.1117/12.2258384
Show Author Affiliations
Xiang-ting Chen, Henan Univ. (China)
Fan Zhang, Henan Univ. (China)
Ruo-ya Zhang, Henan Univ. (China)


Published in SPIE Proceedings Vol. 10245:
International Conference on Innovative Optical Health Science
Xingde Li; Qingming Luo, Editor(s)

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