Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic studyResearch in context

Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic studyResearch in context

Summary: Background: Identifying patients with clinically significant prostate cancer (csPCa) before biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic performance of traditional transrectal ultrasound (TRUS) for csPCa is relatively limited. This study was aimed...

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Bibliographic Details
Main Authors: Yi-Kang Sun, Bo-Yang Zhou, Yao Miao, Yi-Lei Shi, Shi-Hao Xu, Dao-Ming Wu, Lei Zhang, Guang Xu, Ting-Fan Wu, Li-Fan Wang, Hao-Hao Yin, Xin Ye, Dan Lu, Hong Han, Li-Hua Xiang, Xiao-Xiang Zhu, Chong-Ke Zhao, Hui-Xiong Xu
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:EClinicalMedicine
Subjects:
Clinically significant prostate cancer
Ultrasound video
Three-dimensional convolutional neural network
Two-dimensional convolutional neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2589537023002043

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http://www.sciencedirect.com/science/article/pii/S2589537023002043

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