88
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Feature point tracking and trajectory analysis for video imaging in cell biology.

      1 ,
      Journal of structural biology
      Elsevier BV

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          This paper presents a computationally efficient, two-dimensional, feature point tracking algorithm for the automated detection and quantitative analysis of particle trajectories as recorded by video imaging in cell biology. The tracking process requires no a priori mathematical modeling of the motion, it is self-initializing, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. The efficiency of the algorithm is validated on synthetic video data where it is compared to existing methods and its accuracy and precision are assessed for a wide range of signal-to-noise ratios. The algorithm is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. Its applicability is demonstrated in three case studies involving transport of low-density lipoproteins in endosomes, motion of fluorescently labeled Adenovirus-2 particles along microtubules, and tracking of quantum dots on the plasma membrane of live cells. The present automated tracking process enables the quantification of dispersive processes in cell biology using techniques such as moment scaling spectra.

          Related collections

          Author and article information

          Journal
          J Struct Biol
          Journal of structural biology
          Elsevier BV
          1047-8477
          1047-8477
          Aug 2005
          : 151
          : 2
          Affiliations
          [1 ] Institute of Computational Science, ETH Zürich, 8092 Zürich, Switzerland. sbalzarini@inf.ethz.ch
          Article
          S1047-8477(05)00126-7
          10.1016/j.jsb.2005.06.002
          16043363
          c691bb5a-e433-4cf1-9b3f-94ad1b924274
          History

          Comments

          Comment on this article