Feb 18, 2022 · Our systematic review shows that the CNN models of gastric cancer perform well in detection, classification, segmentation and delineating margins. There is no uniform …

In this work, MR-CNN, IMR-CNN, and IBMR-CNN models were trained and tested on the two datasets to clearly demonstrate the ability of the improved model to detect EGC and segment …

Jun 1, 2024 · In this study, we present a deep learning-based technique for multiclassification of endoscopic images by combining modified GoogLeNet and vision transformer (ViT) models …

Feb 7, 2024 · Computer aided diagnosis will help the doctors to identify the gastric cancer easily. In this paper, a CAD based approach is projected to discriminate and categorize gastric …

Jun 27, 2022 · Gastroscopy is an important step in the diagnosis of early gastric cancer. However, because the morphological manifestations of early gastric cancer are not obv.

In this study, we developed a new system based on convolutional neural network (CNN) to analyze gastric mucosal lesions observed by M-NBI. Methods: A total of 386 images of non …

Oct 20, 2021 · Convolutional neural network (CNN) models have recently shown promising performance in analyzing medical images, including endoscopy. This study shows that an …

This research aims to utilize endoscopic images to identify various gastric disorders using an advanced Convolutional Neural Network (CNN) model. The Kvasir dataset, comprising images …

Apr 30, 2025 · Background Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC …

Nov 1, 2017 · Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided …