Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: The World Health Organization (WHO) grading system of pancreatic neuroendocrine tumor (PNET) plays an important role in the clinical decision. The rarity of PNET often negatively affects the radiological application of deep learning algorithms due to the low availability of radiological images. We tried to investigate the feasibility of predicting WHO grades of PNET on contrast-enhanced magnetic resonance (MR) images by deep learning algorithms.

Authors

  • Xuan Gao
    College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
  • Xiaolin Wang
    Department of Urology, Nantong Tumor Hospital, Nantong, Jiangsu, China.