• DocumentCode
    3682974
  • Title

    Detection of Leukocytes in Intravital Video Microscopy Based on the Analysis of Hessian Matrix Eigenvalues

  • Author

    Bruno C. Gregório ;Ricardo J. Ferrari;Juliana Carvalho Tavares

  • Author_Institution
    Dept. of Comput. Sci., Fed. Univ. of Sao Carlos, Sao Carlos, Brazil
  • fYear
    2015
  • Firstpage
    345
  • Lastpage
    352
  • Abstract
    Detection of rolling and adhered leukocytes in intravital microscopy image sequences is an important task in studies of leukocyte-endothelial interactions in the microcirculation of living small animals under different inflammatory conditions. This procedure is usually performed by visual assessment of the image sequences. However, despite being tedious and time consuming, this procedure is prone to the inter- and intra-observer variability. In this work, we developed an automated computer system for the detection of leukocytes in intravital video microscopy. First, the video frames were processed by the bilateral filter to reduce noise while preserving sharp edges. Then, a demons-based image registration technique was applied to minimize animal motion. Finally, the detection of leukocytes was performed by local analysis of Hessian matrix Eigen values. Quantitative and qualitative evaluation of the proposed method were conducted by using 220 video frames obtained from an experimental study performed on the brain microvasculature of mice. The proposed method was compared with the template matching technique using precision, recall and F1-Score measures. For the Hessian-based method, the results of precision, recall and F1-Score were, respectively, equal to 0.81, 0.86, and 0.83. For direct comparison, the results obtained for the template matching technique were 0.86, 0.73 and 0.79.
  • Keywords
    "Microscopy","Eigenvalues and eigenfunctions","Animals","Image sequences","Image registration","Visualization","Shape"
  • Publisher
    ieee
  • Conference_Titel
    Graphics, Patterns and Images (SIBGRAPI), 2015 28th SIBGRAPI Conference on
  • Electronic_ISBN
    1530-1834
  • Type

    conf

  • DOI
    10.1109/SIBGRAPI.2015.48
  • Filename
    7314583