Endoscopic images of varying anatomic features of the Gi tract, challenges their accurate classification ... The purpose of this work was to develop a deep learning model using convolutional neural ...

As a part of this system development, we create a classifier that classifies lesion images into NICE (NBI International Colorectal Endoscopic) classification using deep learning. We developed a ...

However, there are still some problems in the automatic classification of gastric lesions based on deep learning. First ... consent from patients was not required. Endoscopic images were captured ...

The collection of images are classified into three important anatomical landmarks and three clinically significant findings. Detection and classification ... endoscopic medical images. The model’s ...

We achieved highest accuracy of 94.80% by using VGG- 16 to ... the standard of gastroscopy. Deep learning has great potential in gastritis image classification for assisting with achieving accurate ...

Here we present a deep-learning (DL) approach for the diagnosis of atrophic gastritis developed and trained using real-world endoscopic images from the proximal ... handcrafted features are fed to a ...

In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep ... adversarial learning, a machine learning method that promotes the emergence of features ...