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Coverage segmentation of 3D thin structures
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2015 (English)In: Image Processing Theory, Tools and Applications (IPTA), 2015 International Conference on, IEEE conference proceedings, 2015, 23-28 p.Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

We present a coverage segmentation method for extracting thin structures in three-dimensional images. The proposed method is an improved extension of our coverage segmentation method for 2D thin structures. We suggest implementation that enables low memory consumption and processing time, and by that applicability of the method on real CTA data. The method needs a reliable crisp segmentation as an input and uses information from linear unmixing and the crisp segmentation to create a high-resolution crisp reconstruction of the object, which can then be used as a final result, or down-sampled to a coverage segmentation at the starting image resolution. Performed quantitative and qualitative analysis confirm excellent performance of the proposed method, both on synthetic and on real data, in particular in terms of robustness to noise.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 23-28 p.
National Category
Medical Image Processing
Research subject
Medical Technology
Identifiers
URN: urn:nbn:se:kth:diva-180467DOI: 10.1109/IPTA.2015.7367089ISI: 000380472700002Scopus ID: 2-s2.0-84963900787ISBN: 978-1-4799-8636-1 (print)OAI: oai:DiVA.org:kth-180467DiVA: diva2:894116
Conference
The fifth International Conference on Image Processing Theory, Tools and Applications - IPTA 2015,10-13 Nov. 2015, Orléans, France
Note

QC 20160115

Available from: 2016-01-14 Created: 2016-01-14 Last updated: 2016-08-23Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf