잠시만 기다려 주세요. 로딩중입니다.

Lesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer

Clinical Endoscopy 2020년 53권 2호 p.127 ~ 131
윤홍진, 김지현,
소속 상세정보
윤홍진 ( Yoon Hong-Jin ) - Soonchunhyang University College of Medicine Department of Internal Medicine
김지현 ( Kim Jie-Hyun ) - Yonsei University College of Medicine Gangnam Severance Hospital Department of Internal Medicine

Abstract


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.

키워드

Artificial intelligence; Convolutional neural networks; Early gastric cancer; Endoscopy; Invasion depth

원문 및 링크아웃 정보

 

등재저널 정보

KCI
KoreaMed
KAMS