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Proceedings Paper

Improved segmentation of abnormal cervical nuclei using a graph-search based approach
Author(s): Ling Zhang; Shaoxiong Liu; Tianfu Wang; Siping Chen; Milan Sonka
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Paper Abstract

Reliable segmentation of abnormal nuclei in cervical cytology is of paramount importance in automation-assisted screening techniques. This paper presents a general method for improving the segmentation of abnormal nuclei using a graph-search based approach. More specifically, the proposed method focuses on the improvement of coarse (initial) segmentation. The improvement relies on a transform that maps round-like border in the Cartesian coordinate system into lines in the polar coordinate system. The costs consisting of nucleus-specific edge and region information are assigned to the nodes. The globally optimal path in the constructed graph is then identified by dynamic programming. We have tested the proposed method on abnormal nuclei from two cervical cell image datasets, Herlev and H and E stained liquid-based cytology (HELBC), and the comparative experiments with recent state-of-the-art approaches demonstrate the superior performance of the proposed method.

Paper Details

Date Published: 19 March 2015
PDF: 7 pages
Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 94200W (19 March 2015); doi: 10.1117/12.2082856
Show Author Affiliations
Ling Zhang, The Univ. of Iowa (United States)
Shenzhen Univ. (China)
Shaoxiong Liu, Peoples Hospital of Nanshan District (China)
Tianfu Wang, Shenzhen Univ. (China)
Siping Chen, Shenzhen Univ. (China)
Milan Sonka, The Univ. of Iowa (United States)

Published in SPIE Proceedings Vol. 9420:
Medical Imaging 2015: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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