Computer-Aided Diagnosis

Brightness-preserving fuzzy contrast enhancement scheme for the detection and classification of diabetic retinopathy disease

[+] Author Affiliations
Niladri Sekhar Datta

Future Institute of Engineering and Management, Department of Information Technology, Kolkata, West Bengal 700150, India

Himadri Sekhar Dutta

Kalyani Government Engineering College, Department of Electronics and Communication Engineering, Kalyani, Nadia, West Bengal 741235, India

Koushik Majumder

West Bengal University of Technology, Department of Computer Science and Engineering, BF 142, Sector 1, Salt Lake, Kolkata, West Bengal 700064, India

J. Med. Imag. 3(1), 014502 (Feb 09, 2016). doi:10.1117/1.JMI.3.1.014502
History: Received March 3, 2015; Accepted December 18, 2015
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Abstract.  The contrast enhancement of retinal image plays a vital role for the detection of microaneurysms (MAs), which are an early sign of diabetic retinopathy disease. A retinal image contrast enhancement method has been presented to improve the MA detection technique. The success rate on low-contrast noisy retinal image analysis shows the importance of the proposed method. Overall, 587 retinal input images are tested for performance analysis. The average sensitivity and specificity are obtained as 95.94% and 99.21%, respectively. The area under curve is found as 0.932 for the receiver operating characteristics analysis. The classifications of diabetic retinopathy disease are also performed here. The experimental results show that the overall MA detection method performs better than the current state-of-the-art MA detection algorithms.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Niladri Sekhar Datta ; Himadri Sekhar Dutta and Koushik Majumder
"Brightness-preserving fuzzy contrast enhancement scheme for the detection and classification of diabetic retinopathy disease", J. Med. Imag. 3(1), 014502 (Feb 09, 2016). ; http://dx.doi.org/10.1117/1.JMI.3.1.014502


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