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Weighted Labels for 3D Image Segmentation

Please always quote using this URN: urn:nbn:de:0297-zib-3828
  • Segmentation tools in medical imaging are either based on editing geometric curves or on the assignment of region labels to image voxels. While the first approach is well suited to describe smooth contours at subvoxel accuracy, the second approach is conceptually more simple and guarantees a unique classification of image areas. However, contours extracted from labeled images typically exhibit strong staircase artifacts and are not well suited to represent smooth tissue boundaries. In this paper we describe how this drawback can be circumvented by supplementing region labels with additional weights. We integrated our approach into an interactive segmentation system providing a well-defined set of manual and semi-automatic editing tools. All tools update both region labels as well as the corresponding weights simultaneously, thus allowing one to define segmentation results at high resolution. We applied our techniques to generate 3D polygonal models of anatomical structures.

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Author:Detlev Stalling, Malte Zöckler, Oliver Sander, Hans-Christian HegeORCiDGND
Document Type:ZIB-Report
Tag:image processing; segmentation
CCS-Classification:I. Computing Methodologies / I.4 IMAGE PROCESSING AND COMPUTER VISION (REVISED) / I.4.6 Segmentation
Date of first Publication:1998/12/22
Series (Serial Number):ZIB-Report (SC-98-39)
Published in:Appeared under the title "Interactive Segmentation of 3D Medical Images with Subvoxel Accuracy" in: Proceedings CAR '1998 Computer Assisted Radiology and Surgery. H. U. Lemke et al. (eds.) Elsevier 1998. ISBN 0444829733
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