[HTML][HTML] Reduced detection rate of artificial intelligence in images obtained from untrained endoscope models and improvement using domain adaptation algorithm
A training dataset that is limited to a specific endoscope model can overfit artificial
intelligence (AI) to its unique image characteristics. The performance of the AI may degrade …
intelligence (AI) to its unique image characteristics. The performance of the AI may degrade …
Artificial intelligence in endoscopy
Y Okagawa, S Abe, M Yamada, I Oda… - Digestive Diseases and …, 2022 - Springer
Artificial intelligence (AI) is rapidly developing in various medical fields, and there is an
increase in research performed in the field of gastrointestinal (GI) endoscopy. In particular …
increase in research performed in the field of gastrointestinal (GI) endoscopy. In particular …
Proceedings from the first global artificial intelligence in gastroenterology and endoscopy summit
Background and Aims Artificial intelligence (AI), specifically deep learning, offers the
potential to enhance the field of GI endoscopy in areas ranging from lesion detection and …
potential to enhance the field of GI endoscopy in areas ranging from lesion detection and …
[HTML][HTML] Density clustering-based automatic anatomical section recognition in colonoscopy video using deep learning
Recognizing anatomical sections during colonoscopy is crucial for diagnosing colonic
diseases and generating accurate reports. While recent studies have endeavored to identify …
diseases and generating accurate reports. While recent studies have endeavored to identify …
Enabling autonomous medical image data annotation: A human-in-the-loop reinforcement learning approach
LC da Cruz, CA Sierra-Franco… - … 16th Conference on …, 2021 - ieeexplore.ieee.org
Deep learning techniques have shown significant contributions to several fields, including
medical image analysis. For supervised learning tasks, the performance of these techniques …
medical image analysis. For supervised learning tasks, the performance of these techniques …
[HTML][HTML] Active learning performance in labeling radiology images is 90% effective
To train artificial intelligence (AI) systems on radiology images, an image labeling step is
necessary. Labeling for radiology images usually involves a human radiologist manually …
necessary. Labeling for radiology images usually involves a human radiologist manually …
CNNs vs. Transformers: Performance and Robustness in Endoscopic Image Analysis
In endoscopy, imaging conditions are often challenging due to organ movement, user
dependence, fluctuations in video quality and real-time processing, which pose …
dependence, fluctuations in video quality and real-time processing, which pose …
[HTML][HTML] EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
In many research areas, scientific progress is accelerated by multidisciplinary access to
image data and their interdisciplinary annotation. However, keeping track of these …
image data and their interdisciplinary annotation. However, keeping track of these …
[HTML][HTML] Artificial intelligence for upper gastrointestinal endoscopy: a roadmap from technology development to clinical practice
Stomach cancer is the third deadliest type of cancer in the world (0.86 million deaths in
2017). In 2035, a 20% increase will be observed both in incidence and mortality due to …
2017). In 2035, a 20% increase will be observed both in incidence and mortality due to …
[HTML][HTML] Deploying automated machine learning for computer vision projects: a brief introduction for endoscopists
N Mahajan, E Holzwanger, JG Brown, TM Berzin - VideoGIE, 2023 - Elsevier
Artificial intelligence (AI) and machine learning (ML) will play a growing role in
gastroenterology. Computer-aided polyp detection is an early example of the how AI/ML can …
gastroenterology. Computer-aided polyp detection is an early example of the how AI/ML can …