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Multiple resolution skeletons.
A R Dill1, M D Levine, P B Noble
1Computer Vision and Robotics Laboratory, McGill Research Centre for Intelligent Machines, McGill University, Montreal, P.Q. H3A 2A7, Canada; Zevatech AG, Bellach, Switzerland.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
Summary
This study introduces a novel algorithm for skeletonizing noisy amorphous blob images, crucial for understanding leukocyte locomotion and pseudopod dynamics. The method effectively filters noise by analyzing skeletons at multiple resolutions, revealing significant shape features.
Area of Science:
- Image analysis
- Computational biology
- Cell biology
Background:
- Leukocyte locomotion is vital for immune response.
- Pseudopods are dynamic, non-rigid cell structures involved in cell movement.
- Analyzing pseudopod morphology requires robust image processing techniques.
Purpose of the Study:
- To develop a new algorithm for computing skeletons of noisy amorphous blob images.
- To model and detect pseudopods for a better understanding of leukocyte locomotion.
- To create a filtered image representation that preserves significant morphological features.
Main Methods:
- A novel skeletonization algorithm is presented for noisy images.
- The algorithm computes skeletons at multiple resolutions.
- It combines region-centered (skeleton) and boundary analysis at varying scales.
Main Results:
- The multi-resolution skeletonization effectively filters noise while retaining significant shape events.
- Skeleton branches persisting across scales indicate globally significant convexities.
- Lower resolution skeletons provide a measure of global convexity, while higher resolutions pinpoint exact locations.
Conclusions:
- The developed algorithm provides a robust method for analyzing the morphology of amorphous shapes like pseudopods.
- Multi-resolution skeleton analysis enhances understanding of cell dynamics and pseudopod function.
- This approach offers a filtered representation of shape, respecting semantic constraints.
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