https://scholars.lib.ntu.edu.tw/handle/123456789/634709
標題: | Prediction of Visual Impairment in Epiretinal Membrane and Feature Analysis: A Deep Learning Approach Using Optical Coherence Tomography | 作者: | Hsia, Yun Lin, Yu Yi Wang, Bo Sin Su, Chung Yen Lai, Ying Hui YI-TING HSIEH |
關鍵字: | artificial intelligence | deep learning | epiretinal membrane | optical coherence tomography | 公開日期: | 11-一月-2023 | 卷: | 12 | 期: | 1 | 來源出版物: | Asia-Pacific Journal of Ophthalmology | 摘要: | Purpose: The aim was to develop a deep learning model for predicting the extent of visual impairment in epiretinal membrane (ERM) using optical coherence tomography (OCT) images, and to analyze the associated features. Methods: Six hundred macular OCT images from eyes with ERM and no visually significant media opacity or other retinal diseases were obtained. Those with best-corrected visual acuity ≤20/50 were classified as "profound visual impairment,"while those with best-corrected visual acuity >20/50 were classified as "less visual impairment."Ninety percent of images were used as the training data set and 10% were used for testing. Two convolutional neural network models (ResNet-50 and ResNet-18) were adopted for training. The t-distributed stochastic neighbor-embedding approach was used to compare their performances. The Grad-CAM technique was used in the heat map generative phase for feature analysis. Results: During the model development, the training accuracy was 100% in both convolutional neural network models, while the testing accuracy was 70% and 80% for ResNet-18 and ResNet-50, respectively. The t-distributed stochastic neighbor-embedding approach found that the deeper structure (ResNet-50) had better discrimination on OCT characteristics for visual impairment than the shallower structure (ResNet-18). The heat maps indicated that the key features for visual impairment were located mostly in the inner retinal layers of the fovea and parafoveal regions. Conclusions: Deep learning algorithms could assess the extent of visual impairment from OCT images in patients with ERM. Changes in inner retinal layers were found to have a greater impact on visual acuity than the outer retinal changes. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/634709 | ISSN: | 2162-0989 | DOI: | 10.1097/APO.0000000000000576 |
顯示於: | 醫學系 |
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