Particle filtering for tracking of GLUT4 vesicles in TIRF microscpy

Xiangping Wu; Wenglong Xu; Dandan Yan

doi:10.1117/12.831433

30 October 2009 Particle filtering for tracking of GLUT4 vesicles in TIRF microscpy

Xiangping Wu, Wenglong Xu, Dandan Yan

Proceedings Volume 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 74972Q (2009) https://doi.org/10.1117/12.831433
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

GLUT4 is responsible for insulin-stimulated glucose uptake into fat cells and description of the dynamic behavior of it can give insight in some working mechanisms and structures of these cells. Quantitative analysis of the dynamical process requires tracking of hundreds of GLUT4 vesicles characterized as bright spots in noisy image sequences. In this paper, a 3D tracking algorithm built in Bayesian probabilistic framework is put forward, combined with the unique features of the TIRF microscopy. A brightness-correction procedure is firstly applied to ensure that the intensity of a vesicle is constant along time and is only affected by spatial factors. Then, tracking is formalized as a state estimation problem and a developed particle filter integrated by a sub-optimizer that steers the particles towards a region with high likelihood is used. Once each tracked vesicle is located in image plane, the depth information of a granule can be indirectly inferred according to the exponential relationship between its intensity and its vertical position. The experimental results indicate that the vesicles are tracked well under different motion styles. More, the algorithm provides the depth information of the tracked vesicle.

Citation Download Citation

Xiangping Wu, Wenglong Xu, and Dandan Yan "Particle filtering for tracking of GLUT4 vesicles in TIRF microscpy", Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74972Q (30 October 2009); https://doi.org/10.1117/12.831433

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KEYWORDS

Particle filters

Particles

Microscopy

Glucose

Image processing

Luminescence

Electronic filtering

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