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Application of a novel Kalman filter based block matching method to ultrasound images for hand tendon displacement estimation

机译:基于Kalman滤波器的块匹配方法在超声图像中应用手肌腱位移估计

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Purpose: Information about tendon displacement is important for allowing clinicians to not only quantify preoperative tendon injuries but also to identify any adhesive scaring between tendon and adjacent tissue. The Fisher-Tippett (FT) similarity measure has recently been shown to be more accurate than the Laplacian sum of absolute differences (SAD) and Gaussian sum of squared differences (SSD) similarity measures for tracking tendon displacement in ultrasound B-mode images. However, all of these similarity measures can easily be influenced by the quality of the ultrasound image, particularly its signal-to-noise ratio. Ultrasound images of injured hands are unfortunately often of poor quality due to the presence of adhesive scars. The present study investigated a novel Kalman-filter scheme for overcoming this problem.
机译:目的:有关肌腱位移的信息对于允许临床医生不仅量化术前肌腱损伤而且识别肌腱和邻近组织之间的任何粘合剂的信息非常重要。 最近被证明的Fisher-Tippett(FT)相似度措施比Laplacian的绝对差异(SAD)和高斯的平方差别(SSD)相似度测量的相似度措施更准确(SSD)相似度措施,用于跟踪超声波B模式图像中的肌腱位移。 然而,所有这些相似度措施都可以容易地受超声图像质量的影响,特别是其信噪比。 不幸的是,由于粘合剂疤痕的存在,受伤手的超声图像通常往往差。 本研究调查了一种克服这个问题的新型卡尔曼过滤器方案。

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