Quality gaps in public pancreas imaging datasets: Implications & challenges for AI applications.

Journal: Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Published Date: Apr 2, 2021

Abstract

OBJECTIVE: Quality gaps in medical imaging datasets lead to profound errors in experiments. Our objective was to characterize such quality gaps in public pancreas imaging datasets (PPIDs), to evaluate their impact on previously published studies, and to provide post-hoc labels and segmentations as a value-add for these PPIDs.

Authors

  • Garima Suman
    Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA.
  • Anurima Patra
    Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
  • Panagiotis Korfiatis
    From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905.
  • Shounak Majumder
    Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
  • Suresh T Chari
    Department of Gastroenterology, Hepatology and Nutrition, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
  • Mark J Truty
    Department of General and Gastrointestinal Surgery, Mayo Clinic, 200 First Street SW, MN, 55905, USA.
  • Joel G Fletcher
    Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA.
  • Ajit H Goenka
    Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: goenka.ajit@mayo.edu.

Keywords

External Resources

Popular Topics
Recent Journals