Automatic Detection of Microaneurysms in Fundus Images

被引：2

作者：

Astorga, Jesus Eduardo Ochoa ^{[1
]}

Wang, Linni ^{[2
]}

Yamada, Shuhei ^{[1
]}

Fujiwara, Yusuke ^{[1
]}

Du, Weiwei ^{[1
]}

Peng, Yahui ^{[3
]}

机构：

[1] Kyoto Inst Technol, Kyoto, Japan

[2] Tianjin Med Univ Eye Hosp, Tianjin, Peoples R China

[3] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing, Peoples R China

来源：

INTERNATIONAL JOURNAL OF SOFTWARE INNOVATION | 2023年 / 11卷 / 01期

关键词：

Computer Aided Diagnosis; Deep Learning; Diabetic Retinopathy; Retinal Disease;

D O I：

10.4018/IJSI.315658

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Early detection and treatment of diabetic retinopathy can delay blindness and improve quality of life for diabetic patients. It is difficult to detect early symptoms of diabetic retinopathy, which is presented by few microaneurysms in fundus images. This study proposes an algorithm to detect microaneurysms in fundus images automatically. The proposal includes microaneurysms segmentation by U-Net model and their false positives removal by ResNet model. The effectiveness of the proposal is evaluated with the public database IDRiD and E-ophtha by the area under precision recall curve (AUPR). 90% of microaneurysms can be detected at early stages of diabetic retinopathy. This proposal outperforms previous methods based in AUPR evaluation.

引用

页码：26 / 26

页数：1

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