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Proceedings Paper

Automatic choroid cells segmentation and counting in fluorescence microscopic image
Author(s): Jianjun Fei; Weifang Zhu; Fei Shi; Dehui Xiang; Xiao Lin; Lei Yang; Xinjian Chen
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Paper Abstract

In this paper, we proposed a method to automatically segment and count the rhesus choroid-retinal vascular endothelial cells (RF/6A) in fluorescence microscopic images which is based on shape classification, bottleneck detection and accelerated Dijkstra algorithm. The proposed method includes four main steps. First, a thresholding filter and morphological operations are applied to reduce the noise. Second, a shape classifier is used to decide whether a connected component is needed to be segmented. In this step, the AdaBoost classifier is applied with a set of shape features. Third, the bottleneck positions are found based on the contours of the connected components. Finally, the cells segmentation and counting are completed based on the accelerated Dijkstra algorithm with the gradient information between the bottleneck positions. The results show the feasibility and efficiency of the proposed method.

Paper Details

Date Published: 23 March 2016
PDF: 8 pages
Proc. SPIE 9791, Medical Imaging 2016: Digital Pathology, 97911B (23 March 2016); doi: 10.1117/12.2216172
Show Author Affiliations
Jianjun Fei, Soochow Univ. (China)
Weifang Zhu, Soochow Univ. (China)
Fei Shi, Soochow Univ. (China)
Dehui Xiang, Soochow Univ. (China)
Xiao Lin, Soochow Univ. (China)
Lei Yang, Soochow Univ. (China)
Xinjian Chen, Soochow Univ. (China)

Published in SPIE Proceedings Vol. 9791:
Medical Imaging 2016: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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