Automatic quantification of retinal photoreceptor integrity to predict persistent disease activity in neovascular age-related macular degeneration using deep learning.

Song, Xian; Xu, Qian; Li, Haiming; Fan, Qian; Zheng, Yefeng; Zhang, Qiang; Chu, Chunyan; Zhang, Zhicheng; Yuan, Chenglang; Ning, Munan; Bian, Cheng; Ma, Kai; Qu, Yi

Song, Xian; Xu, Qian; Li, Haiming; Fan, Qian; Zheng, Yefeng; Zhang, Qiang; Chu, Chunyan; Zhang, Zhicheng; Yuan, Chenglang; Ning, Munan; Bian, Cheng; Ma, Kai; Qu, Yi.

Affiliation

Song X; Department of Geriatrics, Qilu Hospital of Shandong University, Jinan, China.
Xu Q; Department of Geriatrics, Qilu Hospital of Shandong University, Jinan, China.
Li H; Department of Geriatrics, Qilu Hospital of Shandong University, Jinan, China.
Fan Q; Department of Geriatrics, Qilu Hospital of Shandong University, Jinan, China.
Zheng Y; Tencent Healthcare, Shenzhen, China.
Zhang Q; Tencent Healthcare, Shenzhen, China.
Chu C; Tencent Healthcare, Shenzhen, China.
Zhang Z; Xiaohe Healthcare, ByteDance, Guangzhou, China.
Yuan C; Tencent Healthcare, Shenzhen, China.
Ning M; Tencent Healthcare, Shenzhen, China.
Bian C; Xiaohe Healthcare, ByteDance, Guangzhou, China.
Ma K; Tencent Healthcare, Shenzhen, China.
Qu Y; Department of Geriatrics, Qilu Hospital of Shandong University, Jinan, China.

Front Neurosci ; 16: 952735, 2022.

Article de En | MEDLINE | ID: mdl-36061600

Mots clés

anti-VEGF therapy; deep learning; image analysis; neovascular age-related macular degeneration; optical coherence tomography; retinal photoreceptor

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Front Neurosci Année: 2022 Type de document: Article Pays d'affiliation: Chine

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