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

Clinical Endoscopy

Jie-Hyun Kim¹  Hong Jin Yoon² 

[1] Division of Gastroenterology, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea;Division of Gastroenterology, Department of Internal Medicine, Soonchunhyang University College of Medicine, Cheonan, Korea;

关键词: artificial intelligence;    convolutional neural networks;    early gastric cancer;    endoscopy;    invasion depth;   

DOI  :  10.5946/ce.2020.046

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown