Segmentation of touching mycobacterium tuberculosis from Ziehl-Neelsen stained sputum smear images

Chao Xu; Dongxiang Zhou; Yunhui Liu

doi:10.1117/12.2209226

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14 December 2015 Segmentation of touching mycobacterium tuberculosis from Ziehl-Neelsen stained sputum smear images

Chao Xu, Dongxiang Zhou, Yunhui Liu

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Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 981210 (2015) https://doi.org/10.1117/12.2209226
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

Touching 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.

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Chao Xu, Dongxiang Zhou, and Yunhui Liu "Segmentation of touching mycobacterium tuberculosis from Ziehl-Neelsen stained sputum smear images", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 981210 (14 December 2015); https://doi.org/10.1117/12.2209226

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