Nerthus: A Bowel Preparation Quality Video Dataset

Konstantin Pogorelov, K. Randel, T. Lange, S. Eskeland, C. Griwodz, Dag Johansen, C. Spampinato, M. Taschwer, M. Lux, P. Schmidt, M. Riegler, P. Halvorsen
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引用次数: 62

Abstract

Bowel preparation (cleansing) is considered to be a key precondition for successful colonoscopy (endoscopic examination of the bowel). The degree of bowel cleansing directly affects the possibility to detect diseases and may influence decisions on screening and follow-up examination intervals. An accurate assessment of bowel preparation quality is therefore important. Despite the use of reliable and validated bowel preparation scales, the grading may vary from one doctor to another. An objective and automated assessment of bowel cleansing would contribute to reduce such inequalities and optimize use of medical resources. This would also be a valuable feature for automatic endoscopy reporting in the future. In this paper, we present Nerthus, a dataset containing videos from inside the gastrointestinal (GI) tract, showing different degrees of bowel cleansing. By providing this dataset, we invite multimedia researchers to contribute in the medical field by making systems automatically evaluate the quality of bowel cleansing for colonoscopy. Such innovations would probably contribute to improve the medical field of GI endoscopy.
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Nerthus:肠准备质量视频数据集
肠道准备(清洁)被认为是结肠镜检查成功的关键先决条件。肠道清洁程度直接影响疾病的发现,并可能影响筛查和随访检查间隔的决定。因此,准确评估肠道准备质量非常重要。尽管使用了可靠和有效的肠道准备量表,但分级可能因医生而异。对肠道清洁进行客观和自动评估将有助于减少这种不平等现象并优化医疗资源的利用。这也将是未来自动内窥镜检查报告的一个有价值的功能。在本文中,我们展示了Nerthus,一个包含胃肠道内部视频的数据集,显示了不同程度的肠道清洁。通过提供这个数据集,我们邀请多媒体研究人员在医学领域做出贡献,使系统自动评估结肠镜检查的肠道清洁质量。这些创新可能有助于改善胃肠道内窥镜的医学领域。
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