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Real-Time Interactive 3D Tumor Segmentation Using a Fast Level-Set Algorithm
KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization. Linköping University. (Medicinsk bildbehandling och visualisering)ORCID iD: 0000-0002-0442-3524
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2015 (English)In: Journal of Medical Imaging and Health Informatics, ISSN 2156-7018, E-ISSN 2156-7026, Vol. 5, no 8, 1998-2002 p.Article in journal (Refereed) PublishedText
Abstract [en]

A new level-set based interactive segmentation framework is introduced, where the algorithm learns the intensity distributions of the tumor and surrounding tissue from a line segment drawn by the user from the middle of the lesion towards the border. This information is used to design a likelihood function, which is then incorporated into the level-set framework as an external speed function guiding the segmentation. The endpoint of the input line segment sets a limit to the propagation of 3D region, i.e., when the zero-level-set crosses this point, the propagation is forced to stop. Finally, a fast level set algorithm with coherent propagation is used to solve the level set equation in real time. This allows the user to instantly see the 3D result while adjusting the position of the line segment to tune the parameters implicitly. The “fluctuating” character of the coherent propagation also enables the contour to coherently follow the mouse cursor’s motion when the user tries to fine-tune the position of the contour on the boundary, where the learned likelihood function may not necessarily change much. Preliminary results suggest that radiologists can easily learn how to use the proposed segmentation tool and perform relatively accurate segmentation with much less time than the conventional slice-by-slice based manual procedure.

Place, publisher, year, edition, pages
American Scientific Publishers, 2015. Vol. 5, no 8, 1998-2002 p.
Keyword [en]
Interactive Image Segmentation, Level Set, Coherent Propagation, Tumor Segmentation
National Category
Medical Image Processing
Research subject
Medical Technology
URN: urn:nbn:se:kth:diva-179910DOI: 10.1166/jmihi.2015.1685ISI: 000368564700072ScopusID: 2-s2.0-84955269162OAI: diva2:890866
Swedish Research Council, 2014-6153Swedish Heart Lung Foundation, 20130625

QC 20160112. QC 20160113. QC 20160216

Available from: 2016-01-05 Created: 2016-01-05 Last updated: 2016-02-16Bibliographically approved

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