Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.

Journal: Neuroendocrinology
Published Date: Sep 13, 2019

Abstract

INTRODUCTION: The pathological grading of pancreatic neuroendocrine neoplasms (pNENs) is an independent predictor of survival and indicator for treatment. Deep learning (DL) with a convolutional neural network (CNN) may improve the preoperative prediction of pNEN grading.

Authors

  • Yanji Luo
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Jie Chen
    School of Basic Medical Sciences, Health Science Center, Ningbo University, Ningbo, China.
  • Chenyu Song
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Jingxian Shen
    Department of Radiology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China.
  • Huanhui Xiao
    School of Biomedical Engineering, Health Science Center, Shenzhen University, Block A2, Xili Campus of Shenzhen University, Shenzhen, China.
  • Minhu Chen
    Department of Gastroenterology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Zi-Ping Li
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Bingsheng Huang
    School of Biomedical Engineering, Shenzhen University Health Sciences Center, Shenzhen, Guangdong 518060, P.R.China.
  • Shi-Ting Feng
    Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

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