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Proceedings Paper

General-purpose software tool for serial segmentation of stacked images
Author(s): Vikram Chalana; Michael Sannella; David R. Haynor
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Paper Abstract

Many medical imaging modalities produce spatial or temporal stacks of image data. Segmentation of such image stacks has many applications ranging from quantitative measurements to surgical and radiation treatment planning. The key idea presented in this paper is that of propagating information serially from one slice to the next within an interactive framework. Since information on adjacent slices is very similar, segmentation on one slice can be propagated with slight modification to adjacent slices. The segmentation algorithms that we have developed within this framework are all based on energy minimization principles with an additional constraint that the segmentation on a given image slice is similar to the segmentation predicted from the previous image slice. An optical flow approach is used to predict segmentation from one slice to the next. Three types of algorithms have been developed within the above paradigm for different applications --(1) A Mumford and Shah energy- minimizing algorithm combining edge and region information in a region-growing framework, (2) an active contour model-based tracking method, and (3) an algorithm based on pixel classification and Markov random fields. We recognize the fact that interactivity is very important in medical image segmentation. Therefore, our segmentation tools are available in a Java-based graphical user interface (GUI), allowing users to initialize various segmentation algorithms or to edit the results of automatic segmentation, if desired.

Paper Details

Date Published: 6 June 2000
PDF: 12 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387675
Show Author Affiliations
Vikram Chalana, MathSoft Inc. (United States)
Michael Sannella, MathSoft Inc. (United States)
David R. Haynor, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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