Segmentation of Touching Mycobacterium Tuberculosis from Ziehl-Neelsen Stained Sputum Smear Images
Refereed conference paper presented and published in conference proceedings

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AbstractTouching Mycobacterium tuberculosis objects in the Ziehl-Neelsen stained sputum smear images present different shapes and invisible boundaries in the adhesion areas, which increases the difficulty in objects recognition and counting. In this paper, we present a segmentation method of combining the hierarchy tree analysis with gradient vector flow snake to address this problem. The skeletons of the objects are used for structure analysis based on the hierarchy tree. The gradient vector flow snake is used to estimate the object edge. Experimental results show that the single objects composing the touching objects are successfully segmented by the proposed method. This work will improve the accuracy and practicability of the computer-aided diagnosis of tuberculosis.
All Author(s) ListXu C, Zhou DX, Liu YH
Name of Conference9th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Automatic Target Recognition and Navigation
Start Date of Conference31/10/2015
End Date of Conference01/11/2015
Place of ConferenceEnshi
Country/Region of ConferenceChina
Journal nameProceedings of SPIE
Volume Number9812
LanguagesEnglish-United Kingdom
Keywordscomputer-aided diagnosis; GVF snake; touching objects segmentation; tuberculosis
Web of Science Subject CategoriesOptics; Physics; Physics, Applied

Last updated on 2020-22-11 at 00:09