A review of deep learning and radiomics approaches for pancreatic cancer diagnosis from medical imaging.

Journal: Current opinion in gastroenterology
Published Date: Jul 18, 2023

Abstract

PURPOSE OF REVIEW: Early and accurate diagnosis of pancreatic cancer is crucial for improving patient outcomes, and artificial intelligence (AI) algorithms have the potential to play a vital role in computer-aided diagnosis of pancreatic cancer. In this review, we aim to provide the latest and relevant advances in AI, specifically deep learning (DL) and radiomics approaches, for pancreatic cancer diagnosis using cross-sectional imaging examinations such as computed tomography (CT) and magnetic resonance imaging (MRI).

Authors

  • Lanhong Yao
    Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University.
  • Zheyuan Zhang
    Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University.
  • Elif Keles
    Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University.
  • Cemal Yazici
    Division of Gastroentrrology and Hepatology, University of Illinois Chicago, Chicago, Illinois.
  • Temel Tirkes
    Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N. University Blvd. Suite 0663, Indianapolis, IN, 46202, USA. atirkes@iu.edu.
  • Ulas Bagci
    Department of Radiology, Feinberg School of Medicine, Northwestern University, 737 N Michigan Ave, Ste 1600, Chicago, IL 60611.

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