Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning

Menglin Guo; Mei Zhao; Allen M. Y. Cheong; Houjiao Dai; Andrew Lam; Yongjin Zhou

doi:10.1186/s42492-019-0031-8

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Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning

Menglin Guo Mei Zhao Allen M. Y. Cheong Houjiao Dai Andrew Lam Yongjin Zhou

Year: 2019 Journal: Visual Computing for Industry Biomedicine and Art Vol: 2 (1)Pages: 21-21 Publisher: Springer Nature

DOI: 10.1186/s42492-019-0031-8

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Keywords:

Artificial intelligence Segmentation Optical coherence tomography Computer science Computer vision Deep learning Robustness (evolution) Sørensen–Dice coefficient Image segmentation Pixel Pattern recognition (psychology) Medicine Radiology

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Retinal Imaging and Analysis

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Optical Coherence Tomography Applications

Physical Sciences → Engineering → Biomedical Engineering

Retinal Diseases and Treatments

Health Sciences → Medicine → Ophthalmology

Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning

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