Automated classification between age-related macular degeneration and Diabetic macular edema in OCT image using image segmentation
© 2014 IEEE. Age-related macular degeneration (AMD) and Diabetic macular edema (DME) are to lead causes to make a visual loss in people. People are suffered from the use of many time to diagnose and to wait for treatment both of diseases. This paper proposes a step of image segmentation to be divide...
Saved in:
| Main Authors: | , , |
|---|---|
| 其他作者: | |
| 格式: | Conference or Workshop Item |
| 出版: |
2018
|
| 主題: | |
| 在線閱讀: | https://repository.li.mahidol.ac.th/handle/123456789/35919 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Mahidol University |
| 總結: | © 2014 IEEE. Age-related macular degeneration (AMD) and Diabetic macular edema (DME) are to lead causes to make a visual loss in people. People are suffered from the use of many time to diagnose and to wait for treatment both of diseases. This paper proposes a step of image segmentation to be divided the optical coherence tomography (OCT) to find the retinal pigment epithelium (RPE) layer and to detect a shape of drusen in RPE layer. Then, the RPE layer is used for finding retinal nerve fiber layer (RNFL) and for detecting a bubble of blood area in RNFL complex. Finally, this method uses a binary classification to classify two diseases characteristic between AMD and DME. We use 16 OCT images of a case study to segmentation and classify two diseases. In the experimental results, 10 images of AMD and 6 images of DME can be detected and classified to accuracy of 87.5%. |
|---|