Empirical Study on Myopia Identification Using CNN Hereditary Model for Resource Constrained Ophthalmology
Refractive errors, which include myopia, hyperopia, presbyopia, and astigmatism, are common vision problems that result in blurred vision when light rays are not focused correctly on the retinal plane. Diagnosis and classification of refractive errors are essential for providing appropriate correcti...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Bulgarian Academy of Sciences
2025-03-01
|
| Series: | International Journal Bioautomation |
| Subjects: | |
| Online Access: | http://www.biomed.bas.bg/bioautomation/2025/vol_29.1/files/29.1_02.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Refractive errors, which include myopia, hyperopia, presbyopia, and astigmatism, are common vision problems that result in blurred vision when light rays are not focused correctly on the retinal plane. Diagnosis and classification of refractive errors are essential for providing appropriate corrective measures such as glasses or contact lenses. The key objective of this research is to establish an efficient and fast approach to identifying a refractive defect and categorizing them. Leveraging the capabilities of modern technology, we utilize a smartphone’s camera to capture pictures of the red reflex in the eye. During capturing, the photos are processed using recent image processing techniques to identify any irregularities or asymmetries that may indicate refractive errors. By comparing our method to other current models, we hope to illustrate the advantage of our Hereditary model, which combines a random forest and a convolutional neural network, in accurately diagnosing and classifying refractive errors. Additionally, the proposed approach can serve as a foundation in order to do additional research and development in machine learning and image processing methods improvements for the classification of ocular disorders. |
|---|---|
| ISSN: | 1314-1902 1314-2321 |