Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT.

Journal: European journal of radiology
Published Date: Mar 19, 2021

Abstract

OBJECTIVE: To construct a deep-learning convolution neural network (DL-CNN) system for the differentiation of muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC) on contrast-enhanced computed tomography (CT) images in patients with bladder cancer.

Authors

  • Yuhan Yang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: yyh_1023@163.com.
  • Xiuhe Zou
    Department of Thyroid Surgery, West China Hospital of Sichuan University, Chengdu 610041, PR China.
  • Yixi Wang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: 653508203@qq.com.
  • Xuelei Ma

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