Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testic...

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Detalhes bibliográficos

Principais autores:	Jia-Ying Hu, Zhen-Zhe Lin, Li Ding, Zhi-Xing Zhang, Wan-Ling Huang, Sha-Sha Huang, Bin Li, Xiao-Yan Xie, Ming-De Lu, Chun-Hua Deng, Hao-Tian Lin, Yong Gao, Zhu Wang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Wolters Kluwer Medknow Publications 2025-03-01
coleção:	Asian Journal of Andrology
Assuntos:	azoospermia deep learning male infertility testicular histology ultrasound
Acesso em linha:	https://journals.lww.com/10.4103/aja202480
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