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Active contour based segmentation of resected livers in CT images

: Oelmann, Simon; Oyarzun Laura, Cristina; Drechsler, Klaus; Wesarg, Stefan


Ourselin, S. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Medical imaging 2015. Image processing. Pt.1 : 24 - 26 February 2015, Orlando, Florida, United States
Bellingham, WA: SPIE, 2015 (Proceedings of SPIE 9413)
ISBN: 978-1-62841-503-2
Paper 941316, 6 pp.
Conference "Medical Imaging - Image Processing" <2015, Orlando/Fla.>
Conference Paper
Fraunhofer IGD ()
Business Field: Visual decision support; Research Area: Computer vision (CV); liver; segmentation; snake; medical imaging

The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the active contour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.