Computer‐aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI

Background Deep learning is the most promising methodology for automatic computer‐aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp‐MRI). Purpose To develop an automatic approach based on deep convolutional neural network (DCNN) to classify PCa and noncancerous tissues (NC) with...

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Veröffentlicht in:	Journal of magnetic resonance imaging Jg. 48; H. 6; S. 1570 - 1577
Hauptverfasser:	Song, Yang, Zhang, Yu‐Dong, Yan, Xu, Liu, Hui, Zhou, Minxiong, Hu, Bingwen, Yang, Guang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Wiley Subscription Services, Inc 01.12.2018
Schlagworte:	Artificial neural networks Cancer Confidence intervals Decision analysis deep convolutional neural network Diagnosis Diagnostic systems Diffusion coefficient enhanced prediction Machine learning Magnetic resonance imaging Mathematical models Medical imaging mp‐MRI multiparametric magnetic resonance imaging Neural networks Patients Performance prediction Prostate cancer Rank tests Sensitivity Statistical analysis Statistical tests Statistics prostate cancer mp-MRI deep convolutional neural network enhanced prediction multiparametric magnetic resonance imaging
ISSN:	1053-1807, 1522-2586, 1522-2586
Online-Zugang:	Volltext
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