An angle independent pattern recognition algorithm for ultrasound image blood flow estimation

The authors present an 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: an object recognition phase, in which the speckle patterns of platelets, red blood cells, and white blood cells are identified as contiguous objects, and 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. The advantages of this algorithm over others are discussed, emphasizing the accuracy, robustness to background noise, and low computational needs. Both simulated and real-data tests and results are presented. The algorithm is able to measure the blood flow velocity to 1 pixel/frame accuracy using real data. Future research directions are discussed