Automatic Intravital Video Mining of Rolling and Adhering Leukocytes

In this paper, we present an automatic spatio-temporal mining system of rolling and adherent leukocytes for intravital videos. The magnitude of leukocyte adhesion and the decrease in rolling velocity are common interests for inflammation response studies. Currently, there is no existing system which is perfect for such purposes. Our approach starts with locating moving leukocytes by probabilistic learning of temporal features. It then removes noises through median and location-based filtering, and finally performs motion correspondence through centroid trackers. By extracting the information about moving leukocytes first, we are able to extract adherent leukocytes in a more robust way with an adaptive threshold method. The effectiveness and the efficiency of the proposed method are demonstrated by the experimental results