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Shape-Guided Active Contour Based Segmentation and Tracking of Lumbar Vertebrae in Video Fluoroscopy Using Complex Wavelets

机译:基于形状导向的主动轮廓基于基于活动轮廓的视频荧光透视中腰椎跟踪使用复杂小波

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This paper presents a novel shape-guided active contour based approach for segmenting and tracking lumbar vertebrae in video fluoroscopy using complex-valued wavelets, representations. Due to low radiation exposure levels, fluoroscopic images are characterized by low signal-to-noise ratios, low contrast resolution, and illumination non-homogeneities both spatially and temporally, making current methods ill-suited for segmenting and tracking lumbar vertebrae based on existing energy functionals. Furthermore, current methods perform poorly in situations characterized by high curvature as found in the structure of lumbar spine vertebrae. In this paper, a novel iterative estimation approach is used to determine an external energy functional based on complex wavelets. A shaped-guided algorithm is used to evolve the contour around a lumbar spine vertebra based on the complex wavelet energy. The high curvature exhibited by the lumbar spine vertebra is addressed through a novel importance sampling scheme. Experimental results show that the proposed algorithm achieves significantly better segmentation and tracking performance for lumbar spine vertebrae in fluoroscopic images when compared to existing techniques.
机译:本文介绍了一种新的形状引导的基于主动轮廓的基于主动轮廓,用于使用复值小波,表示的视频荧光透视方法分割和跟踪腰椎椎骨。由于低辐射曝光水平,荧光透视图像的特征在于,在空间和时间上的低信噪比,低对比度分辨率和照明非均匀性,使得基于现有能量的分段和跟踪腰椎的电流方法功能。此外,目前的方法在腰椎椎骨结构中发现的高曲率的情况下表现不佳。本文采用一种新颖的迭代估计方法来基于复杂小波确定外部能量函数。一种形状引导的算法用于基于复杂的小波能量在腰椎椎骨周围的轮廓。腰椎椎骨表现出的高曲率通过新颖的重要抽样方案来解决。实验结果表明,与现有技术相比,该算法在荧光型图像中的腰椎椎骨中的显着更好的分割和跟踪性能。

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