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Proceedings Paper

3D contour based local manual correction of tumor segmentations in CT scans
Author(s): Frank Heckel; Jan Hendrik Moltz; Lars Bornemann; Volker Dicken; Hans-Christian Bauknecht; Michael Fabel; Markus Hittinger; Andreas Kießling; Stephan Meier; Michael Püsken; Heinz-Otto Peitgen
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Paper Abstract

Segmentation is an essential task in medical image analysis. For example measuring tumor growth in consecutive CT scans based on the volume of the tumor requires a good segmentation. Since manual segmentation takes too much time in clinical routine automatic segmentation algorithms are typically used. However there are always cases where an automatic segmentation fails to provide an acceptable segmentation for example due to low contrast, noise or structures of the same density lying close to the lesion. These erroneous segmentation masks need to be manually corrected. We present a novel method for fast three-dimensional local manual correction of segmentation masks. The user needs to draw only one partial contour which describes the lesion's actual border. This two-dimensional interaction is then transferred into 3D using a live-wire based extrapolation of the contour that is given by the user in one slice. Seed points calculated from this contour are moved to adjacent slices by a block matching algorithm. The seed points are then connected by a live-wire algorithm which ensures a segmentation that passes along the border of the lesion. After this extrapolation a morphological postprocessing is performed to generate a coherent and smooth surface corresponding to the user drawn contour as well as to the initial segmentation. An evaluation on 108 lesions by six radiologists has shown that our method is both intuitive and fast. Using our method the radiologists were able to correct 96.3% of lesion segmentations rated as insufficient to acceptable ones in a median time of 44s.

Paper Details

Date Published: 27 March 2009
PDF: 9 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72593L (27 March 2009); doi: 10.1117/12.812248
Show Author Affiliations
Frank Heckel, Fraunhofer MEVIS (Germany)
Jan Hendrik Moltz, Fraunhofer MEVIS (Germany)
Lars Bornemann, Fraunhofer MEVIS (Germany)
Volker Dicken, Fraunhofer MEVIS (Germany)
Hans-Christian Bauknecht, Charité Institute for Radiology (Germany)
Michael Fabel, Christian-Albrechts-Univ. (Germany)
Markus Hittinger, Ludwig-Maximilians-Univ. (Germany)
Andreas Kießling, Philipps-Univ. Marburg (Germany)
Stephan Meier, Johannes Gutenberg Univ. (Germany)
Michael Püsken, Westfälische Wilhelms-Univ. Münster (Germany)
Heinz-Otto Peitgen, Fraunhofer MEVIS (Germany)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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