Video Object Tracking in Neural Axons with Fluorescence Microscopy Images
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-20
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Neurofilament is an important type of intercellular cargos transmitted in neural axons.
Given fluorescence microscopy images, existing methods extract neurofilament movement patterns by manual tracking.
In this paper, we describe two automated tracking methods for analyzing neurofilament movement based on two different techniques: constrained particle filtering and tracking-by-detection.
First, we introduce the constrained particle filtering approach.
In this approach, the orientation and position of a particle are constrained by the axon’s shape such that fewer particles are necessary for tracking neurofilament movement than object tracking techniques based on generic particle filtering.
Secondly, a tracking-by-detection approach to neurofilament tracking is presented.
For this approach, the axon is decomposed into blocks, and the blocks encompassing the moving neurofilaments are detected by graph labeling using Markov random field.
Finally, we compare two tracking methods by performing tracking experiments on real time-lapse image sequences of neurofilament movement, and the experimental results show that both methods demonstrate good performance in comparison with the existing approaches, and the tracking accuracy of the tracing-by-detection approach is slightly better between the two.
American Psychological Association (APA)
Yuan, Liang& Zhu, Junda. 2014. Video Object Tracking in Neural Axons with Fluorescence Microscopy Images. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-471049
Modern Language Association (MLA)
Yuan, Liang& Zhu, Junda. Video Object Tracking in Neural Axons with Fluorescence Microscopy Images. Journal of Applied Mathematics No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-471049
American Medical Association (AMA)
Yuan, Liang& Zhu, Junda. Video Object Tracking in Neural Axons with Fluorescence Microscopy Images. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-471049
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-471049