The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists

The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists

Abstract Purpose To compare the diagnostic performance of deep learning models using convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial cancer and to verify suitable imaging conditions. Methods This retrospective study included patients with endometrial cancer or...

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Bibliographic Details
Main Authors: Aiko Urushibara, Tsukasa Saida, Kensaku Mori, Toshitaka Ishiguro, Kei Inoue, Tomohiko Masumoto, Toyomi Satoh, Takahito Nakajima
Format: Article
Language:English
Published: BMC 2022-04-01
Series:BMC Medical Imaging
Subjects:
Endometrial carcinoma
Artificial intelligence
Convolutional neural network
CNN
Magnetic resonance imaging
Online Access:https://doi.org/10.1186/s12880-022-00808-3

Internet

https://doi.org/10.1186/s12880-022-00808-3

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