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Proceedings Paper

Fast approximate surface evolution in arbitrary dimension
Author(s): James Malcolm; Yogesh Rathi; Anthony Yezzi; Allen Tannenbaum
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Paper Abstract

The level set method is a popular technique used in medical image segmentation; however, the numerics involved make its use cumbersome. This paper proposes an approximate level set scheme that removes much of the computational burden while maintaining accuracy. Abandoning a floating point representation for the signed distance function, we use integral values to represent the signed distance function. For the cases of 2D and 3D, we detail rules governing the evolution and maintenance of these three regions. Arbitrary energies can be implemented in the framework. This scheme has several desirable properties: computations are only performed along the zero level set; the approximate distance function requires only a few simple integer comparisons for maintenance; smoothness regularization involves only a few integer calculations and may be handled apart from the energy itself; the zero level set is represented exactly removing the need for interpolation off the interface; and evolutions proceed on the order of milliseconds per iteration on conventional uniprocessor workstations. To highlight its accuracy, flexibility and speed, we demonstrate the technique on intensity-based segmentations under various statistical metrics. Results for 3D imagery show the technique is fast even for image volumes.

Paper Details

Date Published: 11 March 2008
PDF: 9 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69144C (11 March 2008); doi: 10.1117/12.771080
Show Author Affiliations
James Malcolm, Georgia Institute of Technology (United States)
Yogesh Rathi, Brigham and Women's Hospital (United States)
Anthony Yezzi, Georgia Institute of Technology (United States)
Allen Tannenbaum, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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