A Monte Carlo approach to rolling leukocyte tracking in vivo.

Full Abstract

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.

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Author information

Author/s: Cui, Jing (J); Acton, Scott T (ST); Lin, Zongli (Z);

Affiliation: Charles. L. Brown Department of Electrical and Computer Engineering, University of Virginia, 351 McCormick Road, P.O. Box 400743, Charlottesville, VA 22904-4743, USA. jc2qd(-atsign-)virginia.edu

Journal and publication information

Publication Type: Evaluation Studies; Journal Article

Journal: Medical image analysis (Med Image Anal), published in Netherlands. (Language: eng)

Reference: 2006-Aug; vol 10 (issue 4) : pp 598-610

Dates: Created 2006/08/09; Completed 2006/12/21;

PMID: 16876461, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms
Artificial Intelligence
Cell Movement - physiology
Cells, Cultured
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods

Image Interpretation, Computer-Assisted - methods
Leukocytes - cytology; physiology
Microscopy, Video - methods
Monte Carlo Method
Pattern Recognition, Automated - methods
Reproducibility of Results
Sensitivity and Specificity

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