1. Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images

    Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images

    Purpose : To compare the identification of optic nerve head (ONH) structures in optical coherence tomography images by observers and automated algorithms. Methods : ONH images in 24 radial scan sets by optical coherence tomography were obtained in 51 eyes of 29 glaucoma patients and suspects. Masked intraobserver and interobserver comparisons were made of marked endpoints of Bruch's membrane opening (BMO) and the anterior lamina cribrosa (LC). BMO and LC positional markings were compared between observer and automated algorithm. Repeated analysis on 20 eyes by the algorithm was compared. Regional ONH data were derived from the algorithms. Results : Intraobserver difference in ...

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