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PET image improvement using the Patch Confidence K-Nearest Neighbors Filter
KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.ORCID iD: 0000-0002-1831-9285
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In Positron Emission Tomography (PET), the resulted images are highly deteriorated by noise. In this study, we propose a new denoising framework using the Patch Confidence K-Nearest Neighbors Filter (PCKNN) to reduce noise in the sinogram before forwarding it to the reconstruction procedure. This method has been evaluated on a simulated PET image of a phantom, and the performance has been compared with several conventional methods in the literature. The results have shown that the PET image quality can be substantially improved in term of increased signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR

Place, publisher, year, edition, pages
2014. 306-309 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-154345DOI: 10.1109/BHI.2014.6864364ISI: 000346504900073Scopus ID: 2-s2.0-84906877912ISBN: 978-1-4799-2131-7 (print)OAI: oai:DiVA.org:kth-154345DiVA: diva2:756598
Conference
2014 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), June 1-4, Valencia, Spain
Note

QC 20150127

Available from: 2014-10-17 Created: 2014-10-17 Last updated: 2015-01-27Bibliographically approved

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Hamid Muhammed, Hamed

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  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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