oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
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
CT and PET Image Registration: Application to Thorax Area
Experimental Mechanics, Luleå University of Technology, Luleå, Sweden.ORCID iD: 0000-0003-2960-3094
Institute for Advanced Medical Technologies (IAMT), Tehran University of Medical Science, Tehran, Iran.
Department of Medical Physics and Medical Engineering, Isfahan University of Medical Sciences, Isfahan, Iran.
Research Institute for Nuclear Medicine, Tehran University of Medical Science, Tehran, Iran .
Show others and affiliations
2013 (English)In: Journal of Image and Graphics, ISSN 2301-3699, Vol. 1, no 4, p. 171-175Article in journal (Refereed) Published
Abstract [en]

Accurate attenuation correction of emission data is mandatory for quantitative analysis of PET images. One of the main concerns in CT-based attenuation correction (CTAC) of PET data in multimodality PET/CT imaging is misalignment occurred due to respiratory artifact between PET and CT images. In this paper a combined method which is simple and fast is proposed for registration of PET and CT data to correct the effect of this artifact. The algorithm is composed of two step: First step is meant to reduce the noise by applying an adaptive gradient anistropic diffusion filter then using Iterative closest point (ICP) registration method in order to obtain initial estimation to ensure fast and accurate convergence of the algorithm. At the second step, the respiratory related artifact of PET images is greatly reduced by employing Free Form Deformation algorithm based on B-spline which provides more accurate adaptive transformation to align the images.

Place, publisher, year, edition, pages
Engineering and Technology Publishing , 2013. Vol. 1, no 4, p. 171-175
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:oru:diva-72612DOI: 10.12720/joig.1.4.171-175OAI: oai:DiVA.org:oru-72612DiVA, id: diva2:1290084
Available from: 2019-02-19 Created: 2019-02-19 Last updated: 2019-03-12Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Khodadad, Davood

Search in DiVA

By author/editor
Khodadad, Davood
Medical Image Processing

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 83 hits
CiteExportLink to record
Permanent link

Direct link
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