Abstract
Ultra High Frequency Ultrasound (UHFUS) enables the visualization of highly deformable small and medium vessels in the hand. Intricate vessel-based measurements, such as intimal wall thickness and vessel wall compliance, require sub-millimeter vessel tracking between B-scans. Our fast GPU-based approach combines the advantages of local phase analysis, a distance-regularized level set, and an Extended Kalman Filter (EKF), to rapidly segment and track the deforming vessel contour. We validated on 35 UHFUS sequences of vessels in the hand, and we show the transferability of the approach to 5 more diverse datasets acquired by a traditional High Frequency Ultrasound (HFUS) machine. To the best of our knowledge, this is the first algorithm capable of rapidly segmenting and tracking deformable vessel contours in 2D UHFUS images. It is also the fastest and most accurate system for 2D HFUS images.
Abstract (translated)
超高频超声（UHFUS）可以实现手中高度可变形的中小血管的可视化。复杂的基于血管的测量，例如内膜壁厚度和血管壁顺应性，需要在B扫描之间进行亚毫米血管跟踪。我们基于GPU的快速方法结合了局部相位分析，距离正则化水平集和扩展卡尔曼滤波器（EKF）的优势，可快速分割和跟踪变形血管轮廓。我们对手中的35个UHFUS血管序列进行了验证，并且我们展示了通过传统的高频超声（HFUS）机器获得的5个更多样化数据集的方法的可转移性。据我们所知，这是第一种能够快速分割和跟踪2D UHFUS图像中可变形血管轮廓的算法。它也是2D HFUS图像最快，最准确的系统。
URL
https://arxiv.org/abs/1807.08784
