AIMC Topic: Endoscopy, Gastrointestinal

Clear Filters Showing 121 to 130 of 161 articles

Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can ...

Identification of lesion images from gastrointestinal endoscope based on feature extraction of combinational methods with and without learning process.

Medical image analysis
The gastrointestinal endoscopy in this study refers to conventional gastroscopy and wireless capsule endoscopy (WCE). Both of these techniques produce a large number of images in each diagnosis. The lesion detection done by hand from the images above...

Gastroesophageal Reflux Disease Diagnosis Using Hierarchical Heterogeneous Descriptor Fusion Support Vector Machine.

IEEE transactions on bio-medical engineering
A new computer-aided diagnosis method is proposed to diagnose the gastroesophageal reflux disease (GERD) from endoscopic images of the esophageal-gastric junction. To avoid the interferences of different endoscope devices and automatic camera white b...

Evaluation of a novel flexible snake robot for endoluminal surgery.

Surgical endoscopy
BACKGROUND: Endoluminal therapeutic procedures such as endoscopic submucosal dissection are increasingly attractive given the shift in surgical paradigm towards minimally invasive surgery. This novel three-channel articulated robot was developed to o...

Artificial Intelligence-Assisted Daily Quality Control System for the Histologic Diagnosis of Gastrointestinal Endoscopic Biopsies: A 1-Year Experience.

Archives of pathology & laboratory medicine
CONTEXT.—: Seegene Medical Foundation, one of the major clinical laboratories in South Korea, developed SeeDP, an artificial intelligence (AI)-based postanalytic daily quality control (QC) system that reassesses all gastrointestinal (GI) endoscopic b...

Self-supervised learning framework for efficient classification of endoscopic images using pretext tasks.

PloS one
Identifying anatomical landmarks in endoscopic video frames is essential for the early diagnosis of gastrointestinal diseases. However, this task remains challenging due to variability in visual characteristics across different regions and the limite...

AI-luminating Artificial Intelligence in Inflammatory Bowel Diseases: A Narrative Review on the Role of AI in Endoscopy, Histology, and Imaging for IBD.

Inflammatory bowel diseases
Endoscopy, histology, and cross-sectional imaging serve as fundamental pillars in the detection, monitoring, and prognostication of inflammatory bowel disease (IBD). However, interpretation of these studies often relies on subjective human judgment, ...

GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images.

Mathematical biosciences and engineering : MBE
Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpreting endoscopic images, due to their capacity to provide results equivalent to or exceeding those of ...