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ISBI
2006
IEEE

Bayesian tracking for fluorescence microscopic imaging

14 years 11 months ago
Bayesian tracking for fluorescence microscopic imaging
Fluorescence microscopy is a powerful imaging tool for studying molecular dynamics in living cells. For quantitative motion analysis of subcellular structures robust and accurate detection and tracking techniques are necessary. Sequential Monte Carlo methods, also known as Particle Filters (PF), have become a tremendously popular tool to perform tracking in many fields. We propose a PF-based approach for quantitative analysis of subcellular dynamics. This approach utilizes all spatiotemporal information, which is an important advantage over existing methods that separate the object detection and object linking stage. The tracking technique has been evaluated using simulated but highly realistic image sequences, for which ground truth was available, showing that the method is more robust to noise than existing tracking techniques. In addition, evaluation experiments were conducted with real fluorescence microscopy image data acquired for specific biological studies.
Ihor Smal, Wiro J. Niessen, Erik H. W. Meijering
Added 20 Nov 2009
Updated 20 Nov 2009
Type Conference
Year 2006
Where ISBI
Authors Ihor Smal, Wiro J. Niessen, Erik H. W. Meijering
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