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11 July 2007 Multiresolution transform denoising and segmentation of single molecule motility image series
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Abstract
We present a multiresolution transform-based method for the extraction of moving filament trajectories from single molecule motility data. Noise-corrupted fluorescence image series are denoised using the multiscale median transform and trajectories are detected in the denoised data set. The presented method reduces noise more efficiently than 2D-anisotropic diffusion and several wavelet based techniques. Fibre trajectories are extracted by segmentation of the denoised image stacks and non-crossing trajectories are unambiguously identified combining the information of 2D (XY) and 3D (XYT) segmentation. The algorithm is applied and evaluated using experimental data sets - image sequences of fluorescently labeled F-actin molecules and their 2D-trajectories on a myosin coated surface. This so-called 'motility assay' is used to analyse kinetics, biochemical regulation and pharmacological modulation of these biologically relevant molecules. The presented method improves signal-to-background discrimination, facilitates filament identification and finally, may contribute to significantly improve the performance of this assay.
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F. v. Wegner M.D., T. Ober, C. Weber, O. Friedrich M.D., R. H. A. Fink, and M. Vogel "Multiresolution transform denoising and segmentation of single molecule motility image series", Proc. SPIE 6626, Molecular Imaging, 66260Q (11 July 2007); https://doi.org/10.1117/12.728371
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