Kristoffer Mazanti Cold, Anishan Vamadevan, Amihai Heen, Andreas Slot Vilmann, Mustafa Bulut, Bojan Kovacevic, Morten Rasmussen, Lars Konge, Morten Bo Søndergaard Svendsen
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引用次数: 0
Abstract
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 timestamps of the colonoscope path through the colon. The colonoscope contains coils that, through electromagnetic radiance, are translated into magnetic endoscopic imaging of the position while inside the patient, so the entire length of the colonoscope's position of the colonoscopy can be mapped. Such data have already been used to develop the colonoscopy retraction score, which correlates with the adenoma detection rate and the colonoscopy progression score, which correlates with pain experienced pain. Therefore, we provide a database consisting of 1400 clinical colonoscopies and 100 colonoscopies from a simulated setting. These data are freely available and could be used to map the mucosal inspection of the colon, generate heatmaps to ensure an equally distributed inspection, etc.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.