| Status | 已發表Published |
| Microaneurysm (MA) Detection via Sparse Representation Classifier with MA and Non-MA Dictionary Learning | |
Zhang, B. ; Zhang, L.; You, J.; Karray, F.
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| 2010-10-01 | |
| Source Publication | 2010 20th International Conference on Pattern Recognition
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| Abstract | Diabetic retinopathy (DR) is a common complication of diabetes that damages the retina and leads to sight loss if treated late. In its earliest stage, DR can be diagnosed by micro aneurysm (MA). Although some algorithms have been developed, the accurate detection of MA in color retinal images is still a challenging problem. In this paper we propose a new method to detect MA based on Sparse Representation Classifier (SRC). We first roughly locate MA candidates by using multi-scale Gaussian correlation filtering, and then classify these candidates with SRC. Particularly, two dictionaries, one for MA and one for non-MA, are learned from example MA and non-MA structures, and are used in the SRC process. Experimental results on the ROC database show that the proposed method can well distinguish MA from non-MA objects. |
| Keyword | Diabetic retinopathy microaneurysm Sparse Representation Classifier |
| URL | View the original |
| Language | 英語English |
| The Source to Article | PB_Publication |
| PUB ID | 37151 |
| Document Type | Conference paper |
| Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
| Recommended Citation GB/T 7714 | Zhang, B.,Zhang, L.,You, J.,et al. Microaneurysm (MA) Detection via Sparse Representation Classifier with MA and Non-MA Dictionary Learning[C], 2010. |
| APA | Zhang, B.., Zhang, L.., You, J.., & Karray, F. (2010). Microaneurysm (MA) Detection via Sparse Representation Classifier with MA and Non-MA Dictionary Learning. 2010 20th International Conference on Pattern Recognition. |
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