基于深度学习的OCT图像处理研究

Senyue Hao, Gang Hao
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引用次数: 0

摘要

光学相干层析成像(OCT)是一种新的成像技术,可以实现对被测物体的无创层析成像。深度学习是当今计算机视觉领域发展较快的机器学习算法之一。基于深度学习的OCT图像处理是目前的研究热点。本文综述了基于深度学习的OCT图像处理技术的研究进展,包括深度学习在OCT图像识别、图像分割、图像增强和去噪方面的研究。最后提出了基于深度学习的OCT图像处理的未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on OCT Image Processing Based on Deep Learning
Optical coherence tomography (OCT) is a new imaging technique that can realize non-invasive tomography of the measured object. Deep Learning is one of Machine Learning algorithms that advanced in computer vision nowadays. OCT image processing based on deep learning is currently a hot research topic. This paper reviews the research progress of OCT image processing technology based on deep learning, including the research of deep learning in OCT image recognition, image segmentation, image enhancement and denoising. Some future research directions of OCT image processing based on deep learning are given in the end.
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