NCME-Net: Nuclear cataract mask encoder network for intelligent grading using self-supervised learning from anterior segment photographs

Cataracts are a leading cause of blindness worldwide, making accurate diagnosis and effective surgical planning critical. However, grading the severity of the lens nucleus is challenging because deep learning (DL) models pretrained using ImageNet perform poorly when applied directly to medical data...

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Autori principali:	Jiani Zhao, Cheng Wan, Jiajun Li, Zhe Zhang, Weihua Yang, Keran Li
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2024-07-01
Serie:	Heliyon
Soggetti:	Cataract Deep learning Self-supervision Hybrid model
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2405844024107578
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