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...
محفوظ في:
| المؤلفون الرئيسيون: | , , |
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| مؤلفون آخرون: | |
| التنسيق: | Conference or Workshop Item |
| منشور في: |
2018
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://repository.li.mahidol.ac.th/handle/123456789/35919 |
| الوسوم: |
إضافة وسم
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| المؤسسة: | Mahidol University |
| الملخص: | © 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%. |
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