Deep learning analysis for the detection of pancreatic cancer on endosonographic images: a pilot study.

Journal: Journal of hepato-biliary-pancreatic sciences
Published Date: Oct 15, 2020

Abstract

BACKGROUND/PURPOSE: The application of artificial intelligence to clinical diagnostics using deep learning has been developed in recent years. In this study, we developed an original computer-assisted diagnosis (CAD) system using deep learning analysis of EUS images (EUS-CAD), and assessed its ability to detect pancreatic ductal carcinoma (PDAC), using control images from patients with chronic pancreatitis (CP) and those with a normal pancreas (NP).

Authors

  • Ryosuke Tonozuka
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Takao Itoi
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Naoyoshi Nagata
    Endoscopic Center, Tokyo Medical University, Tokyo, Japan.
  • Hiroyuki Kojima
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Atsushi Sofuni
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Takayoshi Tsuchiya
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Kentaro Ishii
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Reina Tanaka
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.
  • Yuichi Nagakawa
  • Shuntaro Mukai
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.

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