Computer‐aided diagnosis of prostate cancer on magnetic resonance imaging using a convolutional neural network algorithm

Objective To develop a computer‐aided diagnosis (CAD) algorithm with a deep learning architecture for detecting prostate cancer on magnetic resonance imaging (MRI) to promote global standardisation and diminish variation in the interpretation of prostate MRI. Patients and Methods We retrospectively...

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Bibliographic Details
Published in:BJU international 2018-09, Vol.122 (3), p.411-417
Main Authors: Ishioka, Junichiro, Matsuoka, Yoh, Uehara, Sho, Yasuda, Yosuke, Kijima, Toshiki, Yoshida, Soichiro, Yokoyama, Minato, Saito, Kazutaka, Kihara, Kazunori, Numao, Noboru, Kimura, Tomo, Kudo, Kosei, Kumazawa, Itsuo, Fujii, Yasuhisa
Format: Article
Language:English
Subjects:
Algorithms
Biopsy
computer‐aided diagnosis
Datasets
deep learning
Diagnosis
Magnetic resonance imaging
neural network
Neural networks
NMR
Nuclear magnetic resonance
PCSM
prostate biopsy
Prostate cancer
ProstateCancer
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Summary:Objective To develop a computer‐aided diagnosis (CAD) algorithm with a deep learning architecture for detecting prostate cancer on magnetic resonance imaging (MRI) to promote global standardisation and diminish variation in the interpretation of prostate MRI. Patients and Methods We retrospectively reviewed data from 335 patients with a prostate‐specific antigen level of
ISSN:1464-4096
1464-410X
DOI:10.1111/bju.14397