19 March 2015 Automatic choroid cells segmentation and counting based on approximate convexity and concavity of chain code in fluorescence microscopic image
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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, Weihua Lu, Xinjian Chen, Xinjian Chen, Weifang Zhu, Weifang Zhu, Lei Yang, Lei Yang, Zhaoyuan Cao, Zhaoyuan Cao, Haoyu Chen, Haoyu 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); doi: 10.1117/12.2081950; https://doi.org/10.1117/12.2081950
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