首页> 外文期刊>International Journal of Artificial Intelligence Tools: Architectures, Languages, Algorithms >AUTOMATIC DETECTION OF SIMILARITIES AND DIFFERENCES BETWEEN SMALL BOWEL POLYPS AND ULCERS WITH A DATA MINING APPROACH IN WIRELESS CAPSULE ENDOSCOPY VIDEOS
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AUTOMATIC DETECTION OF SIMILARITIES AND DIFFERENCES BETWEEN SMALL BOWEL POLYPS AND ULCERS WITH A DATA MINING APPROACH IN WIRELESS CAPSULE ENDOSCOPY VIDEOS

机译:无线胶囊内窥镜视频中的数据挖掘方法自动检测小肠息肉和溃疡之间的相似性和差异

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Over the past decade Wireless Capsule Endoscopy (WCE) technology has become a very useful tool for diagnosing diseases within the human digestive tract. Using WCE physicians can examine the digestive tract in a minimum invasive way searching for pathological abnormalities such as bleeding, polyps, ulcers and Crohn's disease. In order for WCE to be more effective for gastroenterologists, engineers have developed software methods to automatically detect these diseases at high successful rate. Using proposed a synergistic methodology for automatic discovering polyps (protrusions) and ulcers in WCE video frames, a data mining approach is used that offers useful information about ulcers, polyps and normal tissues and their visual similarities. Finally, results of the methodology are given and statistical comparisons are also presented relevant to other works.
机译:在过去的十年中,无线胶囊内窥镜检查(WCE)技术已成为诊断人体消化道疾病的非常有用的工具。使用WCE,医生可以以最小侵入性的方式检查消化道,以寻找病理异常,例如出血,息肉,溃疡和克罗恩病。为了使WCE对肠胃病医生更加有效,工程师们开发了软件方法来以高成功率自动检测这些疾病。使用提出的用于自动发现WCE视频帧中的息肉(突起)和溃疡的协同方法,使用了一种数据挖掘方法,该方法可提供有关溃疡,息肉和正常组织及其视觉相似性的有用信息。最后,给出了该方法的结果,并提出了与其他工作相关的统计比较。

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