Artificial Intelligence in Surveillance of Barrett's Esophagus

Abstract

A study by Waterhouse and colleagues in a previous issue of Cancer Research describes the development and prospective validation of an artificial intelligence approach in conjunction with spectral imaging to enhance endoscopic detection of Barrett's esophagus-related neoplasia. The authors developed a novel spectral endoscope with external optics suitable for routine Barrett's esophagus surveillance with diffuse tissue reflectance to define multispectral data correlated with histopathology. A convolutional neural network was trained on the absis of the spectral signatures acquired as part of a small, prospective clinical trial to distinguish Barrett's esophagus from Barrett's esophagus neoplasia. The results from the study suggest the utility of artificial intelligence for diagnosis of Barrett's esophagus.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 01, 2021
Source ID
10.1158/0008-5472.can-21-1511

Entities

People

  • Anant Madabhushi
  • Joseph E. Willis
  • Paula Toro

Organizations

  • Case Western Reserve University
  • National Center for Research Resources
  • National Heart, Lung, and Blood Institute
  • National Institute of Biomedical Imaging and Bioengineering
  • United States Department of Defense

Tags

Readers

  • Medical Imaging.
  • Neural Network Machine Learning.
  • Trauma Surgery or Emergency Medicine.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks