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Capsule endoscopy video Boundary Detection

机译:胶囊内窥镜视频边界检测

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摘要

Capsule endoscopy (CE) is a recently developed new technology which enables direct visualization of the inner tract of the whole small bowel (SB) in human body. Due to such a breakthrough compared to traditional endoscopy imaging modalities, this device with its size close to a small pill has seen its wide application in hospitals since it was approved for marketing in 2001. However, it is reported that the inspection of the video data produced in each test cost a clinician about two hours on average to examine. To mitigate such a burden for physicians, it is necessary to develop automatic video analysis techniques for CE video. Since a CE video has an average length of about 60,000 frames for each test, it may be beneficial to segment such a long video into meaningful parts. In this study, we investigate the possibility of applying video boundary detection methods for this purpose. Color and textural features are utilized to represent the visual content. The CE video boundary detection is then formulated as a problem of finding local maximal value along the dissimilarity curve for a CE video. Since a CE undergoes a chaotic motion originated from peristalsis of the digestive tract, motion analysis is further taken into account to refine the results produced in the above steps. Preliminary experimental results suggest the possible usage of the proposed scheme for CE video segmentation.
机译:胶囊内窥镜检查(CE)是一项最新开发的新技术,可直接可视化人体中整个小肠(SB)的内部区域。由于与传统的内窥镜成像方法相比具有突破性意义,自2001年获准上市以来,这种尺寸接近于小药丸的设备已在医院中得到广泛应用。但是,据报道,对视频数据的检查在每次测试中产生的平均花费临床医生检查的时间大约为两个小时。为了减轻医生的这种负担,有必要开发用于CE视频的自动视频分析技术。由于CE视频的每次测试平均长度约为60,000帧,因此将如此长的视频分割成有意义的部分可能会有所帮助。在这项研究中,我们调查了为此目的应用视频边界检测方法的可能性。颜色和纹理特征被用来代表视觉内容。然后,将CE视频边界检测公式化为沿着CE视频的相异曲线找到局部最大值的问题。由于CE经历了源自消化道蠕动的混沌运动,因此进一步考虑了运动分析以完善在上述步骤中产生的结果。初步实验结果表明,该建议方案可用于CE视频分割。

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