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使用颜色切片技术在无线胶囊内镜中检测毛细血管扩张症。

Telangiectasia Detection in Wireless Capsule Endoscopy Using the Color Slicing Technique.

作者信息

Ionescu M, Streba C T, Vere C C, Ionescu A G, Rogoveanu I

机构信息

Department of Medical Informatics, University of Medicine and Pharmacy of Craiova, Romania.

Research Center of Gastroenterology and Hepatology,University of Medicine and Pharmacy of Craiova, Romania.

出版信息

Curr Health Sci J. 2017 Jan-Mar;43(1):25-30. doi: 10.12865/CHSJ.43.01.04. Epub 2017 Sep 27.

Abstract

Wireless capsule endoscopy represents a color imaging technology in the field of medical endoscopy that is extensively used to detect lesions of the human digestive tract. It is the golden standard in evaluating small bowel lesions, offering a set of digital snapshots difficult to get using other investigation methods. Its major drawbacks are the time consumed for image analysis and the burden for the physicians that must spot and classify lesions within more than 55000 images. This paper carries out a study on the detection of telangiectasia in the small bowel, based on an adapted color slicing technique applied not only on unique frames, but on series of successive frames, performing a global analysis suitable on partial sequences or entire wireless capsule endoscopy movies. We have quantified the extracted features and determined a weighting algorithm to find telangiectasia lesions. For frames containing potential lesions, we have determined features not only for the global image, but also for the normal mucosa surrounding the lesion extracted from the image. This approach allows the physician to see variations of parameters within a frame or a sequence that contains lesions. Experimental results prove that the algorithm is effective in detecting telangiectasia patterns of different images, with an accuracy of 93.88%, reducing thus the time spent for the analysis of the images acquired by wireless capsule endoscopy.

摘要

无线胶囊内镜是医学内镜领域中的一种彩色成像技术,广泛用于检测人体消化道病变。它是评估小肠病变的金标准,能提供一组使用其他检查方法难以获得的数字快照。其主要缺点是图像分析耗时,且医生要在超过55000张图像中识别和分类病变,负担较重。本文基于一种经过改进的颜色切片技术,不仅应用于单个帧,还应用于一系列连续帧,对小肠中的毛细血管扩张检测进行了研究,该技术可对部分序列或整个无线胶囊内镜视频进行全局分析。我们对提取的特征进行了量化,并确定了一种加权算法来发现毛细血管扩张病变。对于包含潜在病变的帧,我们不仅确定了全局图像的特征,还确定了从图像中提取的病变周围正常黏膜的特征。这种方法使医生能够看到包含病变的帧或序列内参数的变化。实验结果证明,该算法在检测不同图像的毛细血管扩张模式方面是有效的,准确率为93.88%,从而减少了无线胶囊内镜采集图像的分析时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5502/6286723/431e6bfedd79/CHSJ-43-01-025-fig1.jpg

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