Abstract
Segmentation of volumetric computed tomography (CT) datasets facilitates evaluation of 3D CT angiography renderings, particularly with maximum intensity projection displays. This manuscript describes a novel automated bone editing program that uses an interactive watershed transform (IWT) technique to rapidly extract the skeletal structures from the volume. Advantages of this tool include efficient segmentation of large datasets with minimal need for correction. In the first of this two-part series, the principles of the IWT technique are reviewed, followed by a discussion of clinical utility based on our experience.
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David G. Heath, PhD is a part-owner and consultant of Hip Graphics, Inc. Elliot K. Fishman, MD is a co-founder of Hip Graphics, Inc. In addition, he is on the CT advisory board for and receives grant funding from Siemens Medical Solutions
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Heath, D.G., Hahn, H.K., Johnson, P.T. et al. Automated Multidetector Row CT Dataset Segmentation with an Interactive Watershed Transform (IWT) Algorithm: Part 1. Understanding the IWT Technique. J Digit Imaging 21, 408–412 (2008). https://doi.org/10.1007/s10278-007-9085-9
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DOI: https://doi.org/10.1007/s10278-007-9085-9