Model Convolution: A Computational Approach to Digital Image Interpretation-Reference-Cited by-同舟云学术

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Model Convolution: A Computational Approach to Digital Image Interpretation

Published:2010-02-06 Issue:2 Volume:3 Page:163-170
ISSN:1865-5025
Container-title:Cellular and Molecular Bioengineering
language:en
Short-container-title:Cel. Mol. Bioeng.

Author:

Gardner Melissa K.,Sprague Brian L.,Pearson Chad G.,Cosgrove Benjamin D.,Bicek Andrew D.,Bloom Kerry,Salmon E. D.,Odde David J.

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation

Link

http://www.springerlink.com/index/pdf/10.1007/s12195-010-0101-7

Reference31 articles.

1. Agard, D. A., Y. Hiraoka, P. Shaw, and J. W. Sedat. Fluorescence microscopy in three dimensions. Methods Cell Biol. 30:353–377, 1989.

2. Bicek, A. D., E. Tuzel, D. M. Kroll, and D. J. Odde. Analysis of microtubule curvature. Methods Cell Biol. 83:237–268, 2007.

3. Bicek, A. D., et al. Anterograde microtubule transport drives microtubule bending in LLC-PK1 epithelial cells. Mol. Biol. Cell 20(12):2943–2953, 2009.

4. Chan, C. E., and D. J. Odde. Traction dynamics of filopodia on compliant substrates. Science 322:1687–1691, 2008.

5. Dyba, M., and S. W. Hell. Focal spots of size lambda/23 open up far-field fluorescence microscopy at 33 nm axial resolution. Phys. Rev. Lett. 88:163901, 2002.

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