Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • 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
Optimal frequency-based weighting for spectral x-ray projection imaging
KTH, Skolan för teknikvetenskap (SCI), Fysik, Medicinsk bildfysik.ORCID-id: 0000-0001-7253-0164
KTH, Skolan för teknikvetenskap (SCI), Fysik, Medicinsk bildfysik.
KTH, Skolan för teknikvetenskap (SCI), Fysik, Medicinsk bildfysik.ORCID-id: 0000-0002-5092-8822
2015 (Engelska)Ingår i: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 34, nr 3, s. 779-787Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The purpose of this work is to derive a weighting scheme that maximizes the frequency-dependent ideal observer signal-difference-to-noise ratio, commonly referred to as detectability index or Hotelling-SDNR, for spectral X-ray projection imaging. Starting from basic statistical decision theory, optimal frequency-dependent weights are derived for a multiple-bin system and the Hotelling-SDNR calculated. A 28% increase in detectability index is found for high frequency objects when applying optimal frequency-dependent weights instead of pixel-based weights to a simplified model of a silicon detector, decreasing towards 0% for low frequency objects. Simulation results indicate a potentially large increase in detectability for high-frequency object imaging using silicon detectors, thus meriting further evaluations on a real system.

Ort, förlag, år, upplaga, sidor
2015. Vol. 34, nr 3, s. 779-787
Nationell ämneskategori
Annan fysik
Forskningsämne
Medicinsk teknologi
Identifikatorer
URN: urn:nbn:se:kth:diva-160897DOI: 10.1109/TMI.2014.2360932ISI: 000350870700010PubMedID: 25291789Scopus ID: 2-s2.0-84923873993OAI: oai:DiVA.org:kth-160897DiVA, id: diva2:792111
Anmärkning

QC 20150303

Tillgänglig från: 2015-03-03 Skapad: 2015-03-03 Senast uppdaterad: 2020-03-09Bibliografiskt granskad
Ingår i avhandling
1. Quantification and Maximization of Performance Measures for Photon Counting Spectral Computed Tomography
Öppna denna publikation i ny flik eller fönster >>Quantification and Maximization of Performance Measures for Photon Counting Spectral Computed Tomography
2015 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

During my time as a PhD student at the Physics of Medical Imaging group at KTH, I have taken part in the work of developing a photon counting spectrally resolved silicon detector for clinical computed tomography. This work has largely motivated the direction of my research, and is the main reason for my focus on certain issues. Early in the work, a need to quantify and optimize the performance of a spectrally resolved detector was identified. A large part of my work have thus consisted of reviewing conventional methods used for performance quantification and optimization in computed tomography, and identifying which are best suited for the characterization of a spectrally resolved system. In addition, my work has included comparisons of conventional systems with the detector we are developing. The collected result after a little more than four years of work are four publications and three conference papers.

This compilation thesis consists of five introductory chapters and my four publications. The introductory chapters are not self-contained in the sense that the theory and results from all my published work are included. Rather, they are written with the purpose of being a context in which the papers should be read.

The first two chapters treat the general purpose of the introductory chapters, and the theory of computed tomography including the distinction between conventional, non-spectral, computed tomography, and different practical implementations of spectral computed tomography. The second chapter consists of a review of the conventional methods developed for quantification and optimization of image quality in terms of detectability and signal-to-noise ratio, part of which are included in my published work. In addition, the theory on which the method of material basis decomposition is based on is presented, together with a condensed version of the results from my work on the comparison of two systems with fundamentally different practical solutions for material quantification. In the fourth chapter, previously unpublished measurements on the photon counting spectrally resolved detector we are developing are presented, and compared to Monte Carlo simulations. In the fifth and final chapter, a summary of the appended publications is included.

Ort, förlag, år, upplaga, sidor
Stockholm: KTH Royal Institute of Technology, 2015. s. x, 65
Serie
TRITA-FYS, ISSN 0280-316X ; 15:08
Nyckelord
spectral computed tomography, silicon detector, detectability index, photon counting, Hotelling SDNR, material basis decomposition
Nationell ämneskategori
Annan fysik
Identifikatorer
urn:nbn:se:kth:diva-160899 (URN)978-91-7595-465-3 (ISBN)
Disputation
2015-03-27, sal D3, Lindstedtsvägen 5, KTH, Stockholm, 10:00 (Engelska)
Opponent
Handledare
Anmärkning

QC 20150303

Tillgänglig från: 2015-03-03 Skapad: 2015-03-03 Senast uppdaterad: 2015-03-03Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextPubMedScopus

Personposter BETA

Yveborg, MoaMats, Persson

Sök vidare i DiVA

Av författaren/redaktören
Yveborg, MoaHans, BornefalkMats, Persson
Av organisationen
Medicinsk bildfysik
I samma tidskrift
IEEE Transactions on Medical Imaging
Annan fysik

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetricpoäng

doi
pubmed
urn-nbn
Totalt: 141 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • 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