Deep learning algorithms to segment and quantify the choroidal thickness and vasculature in swept-source optical coherence tomography images

Accurate segmentation of choroidal thickness (CT) and vasculature is important to better analyze and understand the choroid-related ocular diseases. In this paper, we proposed and implemented a novel and practical method based on the deep learning algorithms, residual U-Net, to segment and quantify...

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Detalhes bibliográficos

Principais autores:	Gu Zheng, Yanfeng Jiang, Ce Shi, Hanpei Miao, Xiangle Yu, Yiyi Wang, Sisi Chen, Zhiyang Lin, Weicheng Wang, Fan Lu, Meixiao Shen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	World Scientific Publishing 2021-01-01
Colecção:	Journal of Innovative Optical Health Sciences
Assuntos:	deep learning choroid segmentation swept-source optical coherence tomography
Acesso em linha:	http://www.worldscientific.com/doi/epdf/10.1142/S1793545821400022
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