The Segmentation of Glandular Cavity based on K-means and Mathematical Morphology

被引：0
|
作者：
Ma, Yingjun [1 ]
Hassan, Muhammad Umair [1 ]
Niu, Dongmei [1 ]
Wang, Liping [2 ]
机构：
[1] Univ Jinan, Sch Informat Sci & Engn, Jinan 250022, Shandong, Peoples R China
[2] Fourth Peoples Hosp, Dept Obstet & Gynecol, Zhenjiang, Peoples R China
来源：
2017 4TH INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI) | 2017年
基金：
中国国家自然科学基金;
关键词：
MEDICAL IMAGE SEGMENTATION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper presents a new method for the segmentation of glandular cavity. Our method is based on the K-means and mathematical morphology. We have segmented the entire glandular cavity and eliminated many of the interference factors in the gastric glandular image. An important characteristic of our method is that we combined the K-means with the mathematical morphological processing, and carried out the iterative execution which resulted in a gradual refinement, and the algorithm can run in nearly a linear time. Images that are processed using our methods can be more effective in helping doctors diagnose disease.
引用
收藏
页码：1287 / 1291
页数：5
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