Automatic Detection of Microaneurysms and Hemorrhages in Color Eye Fundus Images
This paper presents an approach for automatic detection of microaneurysms and hemorrhages in fundus images. These lesions are considered the earliest signs of diabetic retinopathy. The diabetic retinopathy is a disease caused by diabetes and is considered as the major cause of blindness in working a...
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| Published in | International journal of computer science & information technology Vol. 5; no. 5; pp. 21 - 37 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English Japanese |
| Published |
31.10.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0975-4660 0975-3826 |
| DOI | 10.5121/ijcsit.2013.5502 |
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| Abstract | This paper presents an approach for automatic detection of microaneurysms and hemorrhages in fundus images. These lesions are considered the earliest signs of diabetic retinopathy. The diabetic retinopathy is a disease caused by diabetes and is considered as the major cause of blindness in working age population. The proposed method is based on mathematical morphology and consists in removing components of retinal anatomy to reach the lesions. This method consists of five stages: 1. pre-processing, 2. enhancement of low intensity structures, 3. detection of blood vessels, 4. elimination of blood vessels, and 5. elimination of the fovea. The accuracy of the method was tested on a public database of fundus images, where it achieved satisfactory results, comparable to other methods from the literature, reporting 87.69% and 92.44% of mean sensitivity and specificity, respectively. |
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| AbstractList | This paper presents an approach for automatic detection of microaneurysms and hemorrhages in fundus images. These lesions are considered the earliest signs of diabetic retinopathy. The diabetic retinopathy is a disease caused by diabetes and is considered as the major cause of blindness in working age population. The proposed method is based on mathematical morphology and consists in removing components of retinal anatomy to reach the lesions. This method consists of five stages: 1. pre-processing, 2. enhancement of low intensity structures, 3. detection of blood vessels, 4. elimination of blood vessels, and 5. elimination of the fovea. The accuracy of the method was tested on a public database of fundus images, where it achieved satisfactory results, comparable to other methods from the literature, reporting 87.69% and 92.44% of mean sensitivity and specificity, respectively. |
| Author | Welfer, Daniel Júnior, Sérgio Bortolin |
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| CitedBy_id | crossref_primary_10_1007_s11042_022_12642_4 crossref_primary_10_13005_bpj_1772 crossref_primary_10_1109_JBHI_2020_3011805 crossref_primary_10_1155_2022_7387174 crossref_primary_10_1155_2017_2483137 crossref_primary_10_1109_TMI_2022_3155154 crossref_primary_10_1109_ACCESS_2017_2671918 crossref_primary_10_1007_s10489_022_03476_6 crossref_primary_10_1016_j_clinimag_2016_11_012 crossref_primary_10_1155_2017_9854825 crossref_primary_10_1155_2015_419279 |
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| Title | Automatic Detection of Microaneurysms and Hemorrhages in Color Eye Fundus Images |
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