A Monte Carlo approach to rolling leukocyte tracking in vivo
Tracking the movement of rolling leukocytes in vivo contributes to the understanding of the mechanism of the inflammatory process and to the development of anti-inflammatory drugs. Several roadblocks exist that hinder successful automated tracking including the moving background, the severe image noise and clutter, the occlusion of the target leukocyte by other leukocytes and structures, the jitter caused by the breathing movement of the living animal, and the weak image contrast. In this paper, a Monte Carlo tracker is developed for automatically tracking a single rolling leukocyte in vivo. Based on the leukocyte movement information and the image intensity features, a specialized sample-weighting criterion is tailored to the application. In comparison with a snake-based tracker, our experiments show that, as the noise intensity level increases, the performance of the snake tracker degrades more than that of the Monte Carlo tracker. In cases, where the leukocyte is observed in contact with the vessel wall, the Monte Carlo tracker is less affected by the image clutter. From tracking within 99 intravital microscopic video sequences, the Monte Carlo tracker exhibits superior performance in the reduced localization error and the increased number of frames tracked when compared with the centroid tracker, the correlation tracker and the GVF snake tracker.
monte carlo leukocyte tracking in vivo factored sampling particle filter