Ray Nilanjan, Acton Scott T
Department of Electrical and Computer Engineering, University of Virginia, 351 McCormick Road, Charlottesville, VA 22904, USA.
IEEE Trans Med Imaging. 2004 Dec;23(12):1466-78. doi: 10.1109/TMI.2004.835603.
Recording rolling leukocyte velocities from intravital microscopic video imagery is a critical task in inflammation research and drug validation. Since manual tracking is excessively time consuming, an automated method is desired. This paper illustrates an active contour based automated tracking method, where we propose a novel external force to guide the active contour that takes the hemodynamic flow direction into account. The construction of the proposed force field, referred to as motion gradient vector flow (MGVF), is accomplished by minimizing an energy functional involving the motion direction, and the image gradient magnitude. The tracking experiments demonstrate that MGVF can be used to track both slow- and fast-rolling leukocytes, thus extending the capture range of previously designed cell tracking techniques.
从活体显微镜视频图像中记录滚动白细胞速度是炎症研究和药物验证中的一项关键任务。由于手动跟踪非常耗时，因此需要一种自动化方法。本文阐述了一种基于主动轮廓的自动跟踪方法，我们提出了一种新颖的外力来引导主动轮廓，该外力考虑了血液动力学流动方向。所提出的力场（称为运动梯度向量流，MGVF）的构建是通过最小化一个涉及运动方向和图像梯度幅度的能量泛函来完成的。跟踪实验表明，MGVF可用于跟踪慢速和快速滚动的白细胞，从而扩展了先前设计的细胞跟踪技术的捕获范围。
