Classification prediction of pancreatic cystic neoplasms based on radiomics deep learning models.

Journal: BMC cancer
Published Date: Nov 29, 2022

Abstract

BACKGROUND: Preoperative prediction of pancreatic cystic neoplasm (PCN) differentiation has significant value for the implementation of personalized diagnosis and treatment plans. This study aimed to build radiomics deep learning (DL) models using computed tomography (CT) data for the preoperative differential diagnosis of common cystic tumors of the pancreas.

Authors

  • Wenjie Liang
    Department of Radiology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Wuwei Tian
    College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
  • Yifan Wang
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Pan Wang
  • Yubizhuo Wang
    Department of Radiology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Hongbin Zhang
    School of Electrical Engineering, Nantong University, Nantong 226019, China.
  • Shijian Ruan
    College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
  • Jiayuan Shao
    College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
  • Xiuming Zhang
    Department of Pathology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Danjiang Huang
    Department of Radiology, Taizhou First People's Hospital, Taizhou, Zhejiang, China.
  • Yong Ding
    Department of Vascular Surgery, Institute of Vascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Xueli Bai

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