AIMC Topic: Colon

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CAS-Colon: A Comprehensive Colonoscopy Anatomical Segmentation Dataset for Artificial Intelligence Development.

Scientific data
Artificial intelligence (AI) holds immense potential to transform gastrointestinal endoscopy by reducing manual workload and enhancing procedural efficiency. However, the development of robust AI algorithms is hindered by limited access to high-quali...

Nancy histological index in ulcerative colitis: an interobserver study.

Journal of clinical pathology
The Nancy histological index (NHI) is a measure of disease activity within colorectal biopsies and a predictor of clinical outcome in ulcerative colitis (UC). We measured interobserver agreement (IOA) during NHI scoring of 20 colorectal biopsies in U...

Mapping the colon through the colonoscope's coordinates - The Copenhagen Colonoscopy Coordinate Database.

Scientific data
Colonoscopy is the leading endoscopic technique when it comes to implementing artificial intelligence-based tools to optimize the procedure. However, no database consisting of the colonoscope's coordinates exists, allowing for a mapping with timestam...

Development of a machine learning-based tension measurement method in robotic surgery.

Surgical endoscopy
BACKGROUND: Over 300,000 colorectal surgeries are performed annually in the U.S. with up to 10% complicated by anastomotic leaks, which cause significant morbidity and mortality. Despite its significant association with anastomotic leaks, tension is ...

A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization.

PloS one
Real-time endoscopic rectal lesion characterization employing artificial intelligence (AI) and near-infrared (NIR) imaging of the fluorescence perfusion indicator agent Indocyanine Green (ICG) has demonstrated promise. However, commercially available...

Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.

Scientific reports
Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of colorectal diseases, there remains a large gap between the current state of CCE in clinical practice, and the state of its counterpart optical colonosc...

Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation.

Computers in biology and medicine
With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited ava...

Deep Learning for Classification of Inflammatory Bowel Disease Activity in Whole Slide Images of Colonic Histopathology.

The American journal of pathology
Grading activity of inflammatory bowel disease (IBD) using standardized histopathological scoring systems remains challenging due to limited availability of pathologists with IBD expertise and interobserver variability. In this study, a deep learning...

G-SET-DCL: a guided sequential episodic training with dual contrastive learning approach for colon segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: This article introduces a novel deep learning approach to substantially improve the accuracy of colon segmentation even with limited data annotation, which enhances the overall effectiveness of the CT colonography pipeline in clinical settin...

Evaluating the pathological and clinical implications of errors made by an artificial intelligence colon biopsy screening tool.

BMJ open gastroenterology
OBJECTIVE: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an A...