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Level set based vessel segmentation accelerated with periodic monotonic speed function
Linköping University, Sweden.ORCID iD: 0000-0002-0442-3524
Linköping University, Sweden.ORCID iD: 0000-0002-7750-1917
2011 (English)In: MEDICAL IMAGING 2011:: IMAGE PROCESSING, SPIE - International Society for Optical Engineering, 2011, Vol. 7962, article id UNSP 79621MConference paper, Published paper (Refereed)
Abstract [en]

To accelerate level-set based abdominal aorta segmentation on CTA data, we propose a periodic monotonic speed function, which allows segments of the contour to expand within one period and to shrink in the next period, i.e., coherent propagation. This strategy avoids the contour's local wiggling behavior which often occurs during the propagating when certain points move faster than the neighbors, as the curvature force will move them backwards even though the whole neighborhood will eventually move forwards. Using coherent propagation, these faster points will, instead, stay in their places waiting for their neighbors to catch up. A period ends when all the expanding/shrinking segments can no longer expand/shrink, which means that they have reached the border of the vessel or stopped by the curvature force. Coherent propagation also allows us to implement a modified narrow band level set algorithm that prevents the endless computation in points that have reached the vessel border. As these points' expanding/shrinking trend changes just after several iterations, the computation in the remaining iterations of one period can focus on the actually growing parts. Finally, a new convergence detection method is used to permanently stop updating the local level set function when the 0-level set is stationary in a voxel for several periods. The segmentation stops naturally when all points on the contour are stationary. In our preliminary experiments, significant speedup (about 10 times) was achieved on 3D data with almost no loss of segmentation accuracy.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2011. Vol. 7962, article id UNSP 79621M
Series
Proceedings of SPIE, ISSN 0277-786X ; 7962
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:kth:diva-258844DOI: 10.1117/12.876704ISI: 000294154900056Scopus ID: 2-s2.0-79957978266ISBN: 978-0-81948-504-5 (print)OAI: oai:DiVA.org:kth-258844DiVA, id: diva2:1350271
Conference
Medical Imaging 2011: Image Processing; Lake Buena Vista, FL; United States; 14 February 2011 through 16 February 2011
Note

QC 20190912

Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2019-09-12Bibliographically approved

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Smedby, Örjan

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