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Ultrasound Surface Extraction for Advanced Skin Rendering
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
2013 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This report evaluates possibilities to combine volumetric ultrasound (us) data together with the recent work published on advanced skin rendering techniques. We focus mainly on how to filter us data and localize surfaces within us data. We also evaluate recent skin rendering techniques in order to have a good understanding of what is needed from the us for rendering realistic skin. us data is acquired using sonography and have a low signal-to-noise ratio by nature, this makes it harder to extract surfaces compared to other medical data acquisition methods such as ct and mr. This report present an algorithm which implements a variational classification technique to emphasize surfaces within us and using a rbf network to fit an implicit function to these surfaces. Using this approach presented we have successfully extract smooth meshes from the noisy us data.

Place, publisher, year, edition, pages
2013. , p. 33
Keywords [en]
Ultrasound, Surface Extraction, Surface Reconstruction, Radial Basis Function, Point Cloud Data
National Category
Media and Communication Technology
Identifiers
URN: urn:nbn:se:liu:diva-98681ISRN: LiU-ITN-TEK-A--13/041--SEOAI: oai:DiVA.org:liu-98681DiVA, id: diva2:655285
Subject / course
Media Technology
Uppsok
Technology
Supervisors
Examiners
Available from: 2013-10-10 Created: 2013-10-10 Last updated: 2018-01-11Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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