Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Comparison of Pre- and Post-Reconstruction Denoising Approaches in Positron Emission Tomography
KTH, Skolan för teknik och hälsa (STH), Hälso- och systemvetenskap.
KTH, Skolan för teknik och hälsa (STH), Hälso- och systemvetenskap.ORCID-id: 0000-0002-1831-9285
2016 (Engelska)Ingår i: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, s. 63-68Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In Positron Emission Tomography (PET), image quality is highly degraded by noise. Therefore, two main PETimage denoising approaches can be used: pre- and postreconstruction denoising. In the pre-reconstruction approach the PET sinogram is denoised before forwarding it to the image reconstruction algorithm. On the other hand, the reconstructed PET-image is denoised in the post-reconstruction approach. In this study, comparison of image quality of the resulting images of the pre- and post-reconstruction approaches is performed. In both types of approaches, the Gaussian filter, the Non-Local Means filter (NLM), the Block-Matching and 3D filter (BM3D), the K-Nearest Neighbors Filter (KNN) and the Patch Confidence K-Nearest Neighbors Filter (PCkNN) are utilized. These approaches are evaluated on a simulated PET-phantom dataset, a real-life physical thorax-phantom PET dataset as well as a reallife MicroPET-scan dataset of a mouse. The performance is measured using the Signal-to-Noise Ratio (SNR) in addition to the Contrast-to-Noise Ratio (CNR) in the resulting images.

Ort, förlag, år, upplaga, sidor
IEEE, 2016. s. 63-68
Nyckelord [en]
BM3D, CNR, FB, Image, Denoising, kNN, MLEM, NLM, PCkNN, PET, Positron Emission Tomography, Sinogram Denoising, SNR
Nationell ämneskategori
Medicinsk bildbehandling
Identifikatorer
URN: urn:nbn:se:kth:diva-198190ISI: 000405596400012Scopus ID: 2-s2.0-85017515445ISBN: 978-1-5090-4142-8 (tryckt)OAI: oai:DiVA.org:kth-198190DiVA, id: diva2:1055977
Konferens
THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016)
Anmärkning

QCR 20161214

QC 20170601

Tillgänglig från: 2016-12-13 Skapad: 2016-12-13 Senast uppdaterad: 2017-08-09Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Scopushttp://ibiomed.ugm.ac.id/

Sök vidare i DiVA

Av författaren/redaktören
Yu, SicongHamid Muhammed, Hamed
Av organisationen
Hälso- och systemvetenskap
Medicinsk bildbehandling

Sök vidare utanför DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetricpoäng

isbn
urn-nbn
Totalt: 60 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf