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Identifying Weak Linear Features with the “Coalescing Shortest Path Image Transform”

Published online by Cambridge University Press:  09 November 2011

Pascal Vallotton*
Affiliation:
Division of Mathematics, Informatics, and Statistics, CSIRO, Sydney, Australia
Changming Sun
Affiliation:
Division of Mathematics, Informatics, and Statistics, CSIRO, Sydney, Australia
David Lovell
Affiliation:
Division of Mathematics, Informatics, and Statistics, CSIRO, Sydney, Australia
Martin Savelsbergh
Affiliation:
Division of Mathematics, Informatics, and Statistics, CSIRO, Sydney, Australia
Matthew Payne
Affiliation:
Division of Mathematics, Informatics, and Statistics, CSIRO, Sydney, Australia School of Medicine, University of Western Sydney, Australia
Gerald Muench
Affiliation:
School of Medicine, University of Western Sydney, Australia
*
Corresponding author. E-mail: [email protected]
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Abstract

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the “Coalescing Shortest Path Image Transform” with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features.

Type
Software and Techniques Development
Copyright
Copyright © Microscopy Society of America 2011

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References

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