[HTML][HTML] Artificial intelligence in gastrointestinal endoscopy: The future is almost here
M Alagappan, JRG Brown, Y Mori… - World journal of …, 2018 - ncbi.nlm.nih.gov
Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of
industries and applications. In recent years, researchers have harnessed artificial …
industries and applications. In recent years, researchers have harnessed artificial …
Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review
M Liedlgruber, A Uhl - IEEE reviews in biomedical engineering, 2011 - ieeexplore.ieee.org
Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the
human body. The advent of endoscopic imaging techniques-allowing the acquisition of …
human body. The advent of endoscopic imaging techniques-allowing the acquisition of …
Artificial intelligence using a convolutional neural network for automatic detection of small‐bowel angioectasia in capsule endoscopy images
A Tsuboi, S Oka, K Aoyama, H Saito, T Aoki… - Digestive …, 2020 - Wiley Online Library
Background and Aim Although small‐bowel angioectasia is reported as the most common
cause of bleeding in patients and frequently diagnosed by capsule endoscopy (CE) in …
cause of bleeding in patients and frequently diagnosed by capsule endoscopy (CE) in …
Wireless capsule endoscopy bleeding images classification using CNN based model
Wireless capsule endoscopy (WCE) is an efficient tool to investigate gastrointestinal tract
disorders and perform painless imaging of the intestine. Despite that, several concerns …
disorders and perform painless imaging of the intestine. Despite that, several concerns …
Computer-aided detection of early neoplastic lesions in Barrett's esophagus
Background and study aims: Early neoplasia in Barrett's esophagus is difficult to detect and
often overlooked during Barrett's surveillance. An automatic detection system could be …
often overlooked during Barrett's surveillance. An automatic detection system could be …
Local mesh patterns versus local binary patterns: biomedical image indexing and retrieval
In this paper, a new image indexing and retrieval algorithm using local mesh patterns are
proposed for biomedical image retrieval application. The standard local binary pattern …
proposed for biomedical image retrieval application. The standard local binary pattern …
Spotting malignancies from gastric endoscopic images using deep learning
JH Lee, YJ Kim, YW Kim, S Park, Y Choi, YJ Kim… - Surgical …, 2019 - Springer
Background Gastric cancer is a common kind of malignancies, with yearly occurrences
exceeding one million worldwide in 2017. Typically, ulcerous and cancerous tissues …
exceeding one million worldwide in 2017. Typically, ulcerous and cancerous tissues …
Towards improving diagnosis of skin diseases by combining deep neural network and human knowledge
Background The emergence of the deep convolutional neural network (CNN) greatly
improves the quality of computer-aided supporting systems. However, due to the challenges …
improves the quality of computer-aided supporting systems. However, due to the challenges …
Content-based processing and analysis of endoscopic images and videos: A survey
In recent years, digital endoscopy has established as key technology for medical screenings
and minimally invasive surgery. Since then, various research communities with manifold …
and minimally invasive surgery. Since then, various research communities with manifold …
Multi-scale context-guided deep network for automated lesion segmentation with endoscopy images of gastrointestinal tract
Accurate lesion segmentation based on endoscopy images is a fundamental task for the
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …