Lesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer
Hong Jin Yoon, Jie‐Hyun Kim
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.
Topics & Concepts
Convolutional neural networkMedicineLesionArtificial intelligenceDeep learningCancerEndoscopyRadiologyPrecancerous lesionArtificial neural networkPattern recognition (psychology)PathologyInternal medicineComputer scienceGastric Cancer Management and OutcomesColorectal Cancer Screening and DetectionGastrointestinal Bleeding Diagnosis and Treatment