DocumentCode :
1430847
Title :
Advanced Level-Set-Based Cell Tracking in Time-Lapse Fluorescence Microscopy
Author :
Dzyubachyk, Oleh ; Van Cappellen, Wiggert A. ; Essers, Jeroen ; Niessen, Wiro J. ; Meijering, Erik
Author_Institution :
Med. Centre, Depts. of Med. Inf. & Radiol., Erasmus Univ., Rotterdam, Netherlands
Volume :
29
Issue :
3
fYear :
2010
fDate :
3/1/2010 12:00:00 AM
Firstpage :
852
Lastpage :
867
Abstract :
Cell segmentation and tracking in time-lapse fluorescence microscopy images is a task of fundamental importance in many biological studies on cell migration and proliferation. In recent years, level sets have been shown to provide a very appropriate framework for this purpose, as they are well suited to capture topological changes occurring during mitosis, and they easily extend to higher dimensional image data. This model evolution approach has also been extended to deal with many cells concurrently. Notwithstanding its high potential, the multiple-level-set method suffers from a number of shortcomings, which limit its applicability to a larger variety of cell biological imaging studies. In this paper, we propose several modifications and extensions to the coupled-active-surfaces algorithm, which considerably improve its robustness and applicability. Our algorithm was validated by comparing it to the original algorithm and two other cell segmentation algorithms. For the evaluation, four real fluorescence microscopy image datasets were used, involving different cell types and labelings that are representative of a large range of biological experiments. Improved tracking performance in terms of precision (up to 11%), recall (up to 8%), ability to correctly capture all cell division events, and computation time (up to nine times reduction) is achieved.
Keywords :
biomedical optical imaging; cellular transport; fluorescence; image segmentation; medical image processing; optical microscopy; advanced level set; cell biological imaging; cell division; cell migration; cell proliferation; cell segmentation; cell tracking; coupled active surfaces algorithm; mitosis; multiple level set method; time-lapse fluorescence microscopy; Biological system modeling; Biology computing; Cells (biology); Evolution (biology); Fluorescence; Image segmentation; Labeling; Level set; Microscopy; Robustness; Cell segmentation; cell tracking; fluorescence microscopy; level sets; multiple object tracking; Algorithms; Bayes Theorem; Biological Markers; Cell Division; Cell Movement; Cell Separation; Databases, Factual; Fluorescent Dyes; HeLa Cells; Humans; Luminescent Proteins; Microscopy, Fluorescence; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2009.2038693
Filename :
5423293
Link To Document :
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