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19 March 2015Automatic choroid cells segmentation and counting based on approximate convexity and concavity of chain code in fluorescence microscopic image

Weihua Lu, Xinjian Chen, Weifang Zhu,Lei Yang,Zhaoyuan Cao,Haoyu Chen

Author Affiliations +

Weihua Lu,¹ Xinjian Chen,¹ Weifang Zhu,¹ Lei Yang,¹ Zhaoyuan Cao,¹ Haoyu Chen^2,3

¹Soochow Univ. (China)
²Joint Shantou International Eye Center of Shantou Univ. (China)
³The Chinese Univ. of Hong Kong (China)

Proceedings Volume 9420, Medical Imaging 2015: Digital Pathology; 942010 (2015)https://doi.org/10.1117/12.2081950
Event:SPIE Medical Imaging, 2015, Orlando, Florida, United States

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Abstract

In this paper, we proposed a method based on the Freeman chain code to segment and count rhesus choroid-retinal vascular endothelial cells (RF/6A) automatically for fluorescence microscopy images. The proposed method consists of four main steps. First, a threshold filter and morphological transform were applied to reduce the noise. Second, the boundary information was used to generate the Freeman chain codes. Third, the concave points were found based on the relationship between the difference of the chain code and the curvature. Finally, cells segmentation and counting were completed based on the characteristics of the number of the concave points, the area and shape of the cells. The proposed method was tested on 100 fluorescence microscopic cell images, and the average true positive rate (TPR) is 98.13% and the average false positive rate (FPR) is 4.47%, respectively. The preliminary results showed the feasibility and efficiency of the proposed method.

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Weihua Lu,Xinjian Chen,Weifang Zhu,Lei Yang,Zhaoyuan Cao, andHaoyu Chen"Automatic choroid cells segmentation and counting based on approximate convexity and concavity of chain code in fluorescence microscopic image", Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 942010 (19 March 2015);https://doi.org/10.1117/12.2081950

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