NDLI: Cell image segmentation based on an improved watershed algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ji, Xiaoqiang Li, Yang Cheng, Jiezhang Yu, Yuanhua Wang, Meijiao
Copyright Year	2015
Description	Author affiliation: School of Electronical Information, College of Optical And Electronical Information Changchun, University of Science And Technology. Changchun, China (Wang, Meijiao) \|\| School of Life Science and Technology, Changchun University of Science and Technology, Changchun, China (Ji, Xiaoqiang; Li, Yang; Cheng, Jiezhang; Yu, Yuanhua)
Abstract	The cell image segmentation has very high practical significance in medical diagnosis. But the cell image has the problems of accretive cells, incoherent cell boundary, and the internal cavity that make it difficult to image segmentation. In this paper, a watershed algorithm based on distance transform is proposed to solve images of cells adhesion. Firstly, image enhancement is carried out as the image preprocessing, then the OTSU threshold segmentation is used to rough segment the image, finally the watershed algorithm by optimizing the seed points is adopt for fine segmentation. Experiment results showed that the proposed algorithm is effectively solved the problems of cell adhesion and over-segmentation, the image segmentation accuracy is more than the traditional watershed algorithm, and remained the cell shape in maximum extent. Therefore, the watershed segmentation based on distance transformation transform is practical according to the accretive cell images.
Starting Page	433
Ending Page	437
File Size	493474
Page Count	5
File Format	PDF
e-ISBN	9781467390989
DOI	10.1109/CISP.2015.7407919
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Adaptation models watershed algorithm Adhesives Image edge detection Signal processing algorithms Morphology Transforms distance transform cell Images segmentation seed point
Content Type	Text
Resource Type	Article

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