Diagnosing uterine cervical cancer on a single T2-weighted image: Comparison between deep learning versus radiologists
A Urushibara, T Saida, K Mori, T Ishiguro… - European Journal of …, 2021 - Elsevier
Purpose To compare deep learning with radiologists when diagnosing uterine cervical
cancer on a single T2-weighted image. Methods This study included 418 patients (age
range, 21− 91 years; mean, 50.2 years) who underwent magnetic resonance imaging (MRI)
between June 2013 and May 2020. We included 177 patients with pathologically confirmed
cervical cancer and 241 non-cancer patients. Sagittal T2-weighted images were used for
analysis. A deep learning model using convolutional neural networks (DCNN), called …
cancer on a single T2-weighted image. Methods This study included 418 patients (age
range, 21− 91 years; mean, 50.2 years) who underwent magnetic resonance imaging (MRI)
between June 2013 and May 2020. We included 177 patients with pathologically confirmed
cervical cancer and 241 non-cancer patients. Sagittal T2-weighted images were used for
analysis. A deep learning model using convolutional neural networks (DCNN), called …
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