Fully automated detection and localization of clinically significant prostate cancer on MR images using a cascaded convolutional neural network

Fully automated detection and localization of clinically significant prostate cancer on MR images using a cascaded convolutional neural network

PurposeTo develop a cascaded deep learning model trained with apparent diffusion coefficient (ADC) and T2-weighted imaging (T2WI) for fully automated detection and localization of clinically significant prostate cancer (csPCa).MethodsThis retrospective study included 347 consecutive patients (235 cs...

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Bibliographic Details
Main Authors: Lina Zhu, Ge Gao, Yi Zhu, Chao Han, Xiang Liu, Derun Li, Weipeng Liu, Xiangpeng Wang, Jingyuan Zhang, Xiaodong Zhang, Xiaoying Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Oncology
Subjects:
deep learning
prostatic neoplasms
magnetic resonance imaging
detection
localization
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.958065/full

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