Lesion-based convolutional neural network in diagnosis of early gastric cancer

Hong Jin Yoon, Jie Hyun Kim

Research output: Contribution to journalReview articlepeer-review

18 Citations (Scopus)


Diagnosis and evaluation of early gastric cancer (EGC) using endoscopic images is significantly important; however, it has some limitations. In several studies, the application of convolutional neural network (CNN) greatly enhanced the effectiveness of endoscopy. To maximize clinical usefulness, it is important to determine the optimal method of applying CNN for each organ and disease. Lesion-based CNN is a type of deep learning model designed to learn the entire lesion from endoscopic images. This review describes the application of lesion-based CNN technology in diagnosis of EGC.

Original languageEnglish
Pages (from-to)127-131
Number of pages5
JournalClinical Endoscopy
Issue number2
Publication statusPublished - 2020 Mar

Bibliographical note

Publisher Copyright:
Copyright © 2020 Korean Society of Gastrointestinal Endoscopy

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Gastroenterology


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