1. Diagnosing Glaucoma with Spectral-domain Optical Coherence Tomography Using Deep Learning Classifier

    Diagnosing Glaucoma with Spectral-domain Optical Coherence Tomography Using Deep Learning Classifier

    Précis: An SD-OCT based deep learning system detected glaucomatous structural change with high sensitivity and specificity. It outperformed the clinical diagnostic parameters in discriminating glaucomatous eyes from healthy eyes. Purpose: To assess the performance of a deep learning classifier for detection of glaucomatous change based on spectral-domain optical coherence tomography (SD-OCT). Methods: Three hundred and fifty image sets of ganglion cell-inner plexiform layer (GCIPL) and retinal nerve fiber layer (RNFL) SD-OCT for 86 glaucomatous eyes and 307 SD-OCT image sets of 196 healthy participants were recruited and split into training (197 eyes) and test (85 eyes) datasets based on ...

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