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Proceedings Paper

Local SIMPLE multi-atlas-based segmentation applied to lung lobe detection on chest CT
Author(s): M. Agarwal; E. A. Hendriks; B. C. Stoel; M. E. Bakker; J. H. C. Reiber; M. Staring
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Paper Abstract

For multi atlas-based segmentation approaches, a segmentation fusion scheme which considers local performance measures may be more accurate than a method which uses a global performance measure. We improve upon an existing segmentation fusion method called SIMPLE and extend it to be localized and suitable for multi-labeled segmentations. We demonstrate the algorithm performance on 23 CT scans of COPD patients using a leave-one- out experiment. Our algorithm performs significantly better (p < 0.01) than majority voting, STAPLE, and SIMPLE, with a median overlap of the fissure of 0.45, 0.48, 0.55 and 0.6 for majority voting, STAPLE, SIMPLE, and the proposed algorithm, respectively.

Paper Details

Date Published: 14 February 2012
PDF: 7 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831410 (14 February 2012); doi: 10.1117/12.911552
Show Author Affiliations
M. Agarwal, Leiden Univ. Medical Ctr. (Netherlands)
Delft Univ. of Technology (Netherlands)
E. A. Hendriks, Delft Univ. of Technology (Netherlands)
B. C. Stoel, Leiden Univ. Medical Ctr. (Netherlands)
M. E. Bakker, Leiden Univ. Medical Ctr. (Netherlands)
J. H. C. Reiber, Leiden Univ. Medical Ctr. (Netherlands)
M. Staring, Leiden Univ. Medical Ctr. (Netherlands)

Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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