1. Deep Neural Network for Scleral Spur Detection in Anterior Segment OCT Images: The Chinese American Eye Study

    Deep Neural Network for Scleral Spur Detection in Anterior Segment OCT Images: The Chinese American Eye Study

    Purpose : To develop a deep neural network that detects the scleral spur in anterior segment optical coherence tomography (AS-OCT) images. Methods : Participants in the Chinese American Eye Study, a population-based study in Los Angeles, California, underwent complete ocular examinations, including AS-OCT imaging with the Tomey CASIA SS-1000. One human expert grader provided reference labels of scleral spur locations in all images. A convolutional neural network (CNN)-based on the ResNet-18 architecture was developed to detect the scleral spur in each image. Performance of the CNN model was assessed by calculating prediction errors, defined as the difference between the Cartesian coordinates ...

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