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Red lesion detection using background estimation and lesions characteristics in diabetic retinal image

[+] Author Affiliations
Dongbo Zhang

Xiangtan University, College of Information Engineering, Xiangtan 411105, China

Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education, Xiangtan 411105, China

Yinghui Peng

Xiangtan University, College of Information Engineering, Xiangtan 411105, China

Yao Yi

Xiangtan University, College of Information Engineering, Xiangtan 411105, China

Xingyu Shang

Xiangtan University, College of Information Engineering, Xiangtan 411105, China

J. Electron. Imaging. 22(4), 043024 (Dec 16, 2013). doi:10.1117/1.JEI.22.4.043024
History: Received January 23, 2013; Revised October 10, 2013; Accepted November 13, 2013
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Abstract.  Detection of red lesions [hemorrhages (HRs) and microaneurysms (MAs)] is crucial for the diagnosis of early diabetic retinopathy. A method based on background estimation and adapted to specific characteristics of HRs and MAs is proposed. Candidate red lesions are located by background estimation and Mahalanobis distance measure and then some adaptive postprocessing techniques, which include vessel detection, nonvessel exclusion based on shape analysis, and noise points exclusion by double-ring filter (only used for MAs detection), are conducted to remove nonlesion pixels. The method is evaluated on our collected image dataset, and experimental results show that it is better than or approximate to other previous approaches. It is effective to reduce the false-positive and false-negative results that arise from incomplete and inaccurate vessel structure.

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Citation

Dongbo Zhang ; Yinghui Peng ; Yao Yi and Xingyu Shang
"Red lesion detection using background estimation and lesions characteristics in diabetic retinal image", J. Electron. Imaging. 22(4), 043024 (Dec 16, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.4.043024


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