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    Joint Deep Matching Model of OCT Retinal Layer Segmentation

    Mei Yang1, Yuanjie Zheng1, 2, *, Weikuan Jia1, *, Yunlong He3, Tongtong Che1, Jinyu Cong1

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1485-1498, 2020, DOI:10.32604/cmc.2020.09940

    Abstract Optical Coherence Tomography (OCT) is very important in medicine and provide useful diagnostic information. Measuring retinal layer thicknesses plays a vital role in pathophysiologic factors of many ocular conditions. Among the existing retinal layer segmentation approaches, learning or deep learning-based methods belong to the state-of-art. However, most of these techniques rely on manual-marked layers and the performances are limited due to the image quality. In order to overcome this limitation, we build a framework based on gray value curve matching, which uses depth learning to match the curve for semi-automatic segmentation of retinal layers from OCT. The depth convolution network… More >

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