Improvement of automatic hemorrhage detection methods using brightness correction on fundus images

Yuji Hatanaka; Toshiaki Nakagawa; Yoshinori Hayashi; Masakatsu Kakogawa; Akira Sawada; Kazuhide Kawase; Takeshi Hara; Hiroshi Fujita

doi:10.1117/12.771051

17 March 2008 Improvement of automatic hemorrhage detection methods using brightness correction on fundus images

Yuji Hatanaka, Toshiaki Nakagawa, Yoshinori Hayashi, Masakatsu Kakogawa, Akira Sawada, Kazuhide Kawase, Takeshi Hara, Hiroshi Fujita

Author Affiliations +

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 69153E (2008) https://doi.org/10.1117/12.771051
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

We have been developing several automated methods for detecting abnormalities in fundus images. The purpose of this study is to improve our automated hemorrhage detection method to help diagnose diabetic retinopathy. We propose a new method for preprocessing and false positive elimination in the present study. The brightness of the fundus image was changed by the nonlinear curve with brightness values of the hue saturation value (HSV) space. In order to emphasize brown regions, gamma correction was performed on each red, green, and blue-bit image. Subsequently, the histograms of each red, blue, and blue-bit image were extended. After that, the hemorrhage candidates were detected. The brown regions indicated hemorrhages and blood vessels and their candidates were detected using density analysis. We removed the large candidates such as blood vessels. Finally, false positives were removed by using a 45-feature analysis. To evaluate the new method for the detection of hemorrhages, we examined 125 fundus images, including 35 images with hemorrhages and 90 normal images. The sensitivity and specificity for the detection of abnormal cases was were 80% and 88%, respectively. These results indicate that the new method may effectively improve the performance of our computer-aided diagnosis system for hemorrhages.

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Yuji Hatanaka, Toshiaki Nakagawa, Yoshinori Hayashi, Masakatsu Kakogawa, Akira Sawada, Kazuhide Kawase, Takeshi Hara, and Hiroshi Fujita "Improvement of automatic hemorrhage detection methods using brightness correction on fundus images", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69153E (17 March 2008); https://doi.org/10.1117/12.771051

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