Drozdzal Michal, Seguí Santi, Radeva Petia, Malagelada Carolina, Azpiroz Fernando, Vitrià Jordi
Computer Vision Center (CVC), Barcelona, Spain.
Computer Vision Center (CVC), Barcelona, Spain; Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain.
Comput Biol Med. 2015 Oct 1;65:320-30. doi: 10.1016/j.compbiomed.2015.04.006. Epub 2015 Apr 14.
Wireless Capsule Endoscopy (WCE) provides a new perspective of the small intestine, since it enables, for the first time, visualization of the entire organ. However, the long visual video analysis time, due to the large number of data in a single WCE study, was an important factor impeding the widespread use of the capsule as a tool for intestinal abnormalities detection. Therefore, the introduction of WCE triggered a new field for the application of computational methods, and in particular, of computer vision. In this paper, we follow the computational approach and come up with a new perspective on the small intestine motility problem. Our approach consists of three steps: first, we review a tool for the visualization of the motility information contained in WCE video; second, we propose algorithms for the characterization of two motility building-blocks: contraction detector and lumen size estimation; finally, we introduce an approach to detect segments of stable motility behavior. Our claims are supported by an evaluation performed with 10 WCE videos, suggesting that our methods ably capture the intestinal motility information.
无线胶囊内镜（WCE）为小肠提供了一个全新的视角，因为它首次实现了对整个小肠器官的可视化。然而，由于单次WCE研究中的数据量庞大，导致视觉视频分析时间过长，这是阻碍胶囊作为肠道异常检测工具广泛应用的一个重要因素。因此，WCE的引入引发了计算方法应用的新领域，尤其是计算机视觉领域。在本文中，我们采用计算方法，对小肠运动问题提出了新的观点。我们的方法包括三个步骤：首先，我们回顾一种用于可视化WCE视频中包含的运动信息的工具；其次，我们提出用于表征两种运动组成部分的算法：收缩检测器和管腔大小估计；最后，我们引入一种检测稳定运动行为片段的方法。我们的观点得到了对10个WCE视频进行的评估的支持，这表明我们的方法能够有效地捕捉肠道运动信息。
