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Parallel N-Dimensional Exact Signed Euclidean Distance Transform

Staubs, Robert, Fedorov, Andriy, Linardakis, Leonidas, Dunton, Benjamin, Chrisochoides, Nikos
College of William and Mary
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/307
New: Prefer using the following doi: https://doi.org/10.54294/ogv879
Published in The Insight Journal - 2006 July - December.
Submitted by Robert Staubs on 2006-09-16T09:55:22Z.

The computation speed for distance transforms becomes important in a wide variety of image processing applications. Current ITK library filters do not see any benefit from a multithreading environment. We introduce a three-dimensional signed parallel implementation of the exact Euclidean distance transform algorithm developed by Maurer et al. with a theoretical complexity of O(n/p) for n voxels and p threads. Through this parallelization and efficient use of data structures we obtain approximately 3 times mean speedup on standard tests on a 4-processor machine compared with the current ITK exact Euclidean distance transform filter.