Semi‐Automated Object Tracking Methods in Biological Imaging. Issue 1 (5th January 2015)

• Record Type: Journal Article
• Authors: Davis, Michael A.; Pražský, Ondřej; Sysko, Laura R.
• Editors: Robinson, J. Paul; Darzynkiewicz, Zbigniew; Hoffman, Robert; Nolan, John P.; Rabinovitch, Peter S.; Watkins, Simon
• Is Part Of: Current protocols in cytometry. Volume 71:Issue 1(2015)
• Page Start: 12.38.1
• Page End: 12.38.21
• Publication Date: 2015-01-05
• Subjects: object tracking -- sampling frequency -- image segmentation methods -- object linking -- image analysis -- digital imaging -- single‐particle tracking; Cytology -- Laboratory manuals; Flow cytometry -- Laboratory manuals; Cell separation -- Laboratory manuals; Molecular biology -- Laboratory manuals; Flow Cytometry -- methods; Image Cytometry -- methods; Cell Separation -- methods; Cytological Techniques; Molecular Biology -- methods; Cell separation; Cytology; Flow cytometry; Molecular biology; Laboratory Manuals; Laboratory manuals; 571.6
• DOI: 10.1002/0471142956.cy1238s71
• Languages: English
• ISSNs: 1934-9297

Abstract

Abstract: Time‐lapse imaging is a rich data source offering potential kinetic information of cellular activity and behavior. Tracking and extracting measurements of objects from time‐lapse datasets are challenges that result from the complexity and dynamics of each object's motion and intensity or the appearance of new objects in the field of view. A wide range of strategies for proper data sampling, object detection, image analysis, and post‐analysis interpretation are available. Theory and methods for single‐particle tracking, spot detection, and object linking are discussed in this unit, as well as examples with step‐by‐step procedures for utilizing semi‐automated software and visualization tools for achieving tracking results and interpreting this output. © 2015 by John Wiley & Sons, Inc.