… Next, we review the technological advances of AI in endoscopic imaging such as … AI in
endoscopic imaging in more detail. This discussion includes a brief overview of medical imaging …

… Second, endoscopic images for machine learning of CAD are more easily collected in
the colonoscopy field than in the gastroscopy field because of the large number of positive …

… In contrast to colonoscopy, usage of AI in gastroscopy is currently rather limited. Regarding
other fields of endoscopic imaging, capsule endoscopy is the ideal imaging platform for AI, …

… Some investigations have used magnifying endoscopic images. Further AI studies on the
stomach are expected to contribute to the detection and diagnosis of gastric cancer, because a …

… using 3 different datasets: labeled endoscopic images, white-light endoscopy images of
dysplastic and nondysplastic BE neoplasia, and NBI zoom images. This system resulted in an …

… blue pixel values and utilized endoscopic images for evaluating endoscopic severity of UC.
… histological index, Mayo endoscopic subscore, and UC Endoscopic Index of Severity scores. …

… The DL-BASED MODELS currently available to assist GI endoscopic diagnosis … endoscope
and sweepingly interpreting endoscopic images. Most of the AI systems used for endoscopy …

… key words such as machine learning, deep learning, artificial intelligence, computer-aided
diagnosis, convolutional neural networks, GI endoscopy, and endoscopic image analysis. …

… The EndoBRAIN system was initially trained using 69,142 endocytoscopic images, taken
at 520-fold magnification, from patients with colorectal polyps who underwent endoscopy at 5 …

… in the detection of lesions in static endoscopic images[23]. These … Early grey-level texture
analysis of endoscopic images … wavelet transformation of each image to discriminate amongst …