一种不依赖角度的超声图像血流估计模式识别算法

J. Foster, M. Smith
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引用次数: 3

摘要

作者提出了一种基于超声阵列设备连续散斑图像来确定动脉血流的新算法。该算法由两部分组成:(i)目标识别阶段,其中血小板、红细胞和白细胞的斑点模式被识别为连续的目标;(ii)跟踪阶段,其中选择最大似然方向作为速度矢量的最佳候选。该算法能够从2mhz拍摄的b模式图像中检测到二维运动。当三维阵列技术出现时,该算法可以很容易地适应于三维运动的检测。讨论了该算法相对于现有算法的优点,重点是精度、对背景噪声的鲁棒性和低计算需求。给出了模拟数据和实际数据的测试结果。使用真实数据,该算法能够测量血流速度,精度达到1像素/帧
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An angle independent pattern recognition algorithm for ultrasound image blood flow estimation
The authors present a new algorithm for determining the blood flow in arteries based upon consecutive speckle pattern images from an ultrasound array device. The algorithm is composed of two parts: (i) an object recognition phase in which the speckle patterns of platelets, red blood cells, and white blood cells are identified as contiguous objects: and (ii) a tracking phase in which the maximum likelihood direction is chosen as the best candidate for the velocity vector. The algorithm is able to detect 2-D motion from B-mode images taken at 2 MHz. When 3-D array techniques become available, the algorithm can be easily adapted to detecting 3-D motion. The advantages of this algorithm over existing ones are discussed, with emphasis on accuracy, robustness to background noise, and low computational needs. Both simulated and real data tests and results are presented. Using real data, the algorithm was able to measure the blood flow velocity to 1-pixel/frame accuracy.<>
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