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Updated: Mar 9, 2026
Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow
Published on: May 26, 2023
Machine learning based detection of age-related macular degeneration (AMD) and diabetic macular edema (DME) from
Yu Wang1, Yaonan Zhang2, Zhaomin Yao1
1Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning 110169, China; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China.
Abstract:
Non-lethal macular diseases greatly impact patients' life quality, and will cause vision loss at the late stages. Visual inspection of the optical coherence tomography (OCT) images by the experienced clinicians is the main diagnosis technique. We proposed a computer-aided diagnosis (CAD) model to discriminate age-related macular degeneration (AMD), diabetic macular edema (DME) and healthy macula. The linear configuration pattern (LCP) based features of the OCT images were screened by the Correlation-based Feature Subset (CFS) selection algorithm. And the best model based on the sequential minimal optimization (SMO) algorithm achieved 99.3% in the overall accuracy for the three classes of samples.
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