Literature DB >> 17926967

Empirical dual energy calibration (EDEC) for cone-beam computed tomography.

Philip Stenner1, Timo Berkus, Marc Kachelriess.   

Abstract

Material-selective imaging using dual energy CT (DECT) relies heavily on well-calibrated material decomposition functions. These require the precise knowledge of the detected x-ray spectra, and even if they are exactly known the reliability of DECT will suffer from scattered radiation. We propose an empirical method to determine the proper decomposition function. In contrast to other decomposition algorithms our empirical dual energy calibration (EDEC) technique requires neither knowledge of the spectra nor of the attenuation coefficients. The desired material-selective raw data p1 and p2 are obtained as functions of the measured attenuation data q1 and q2 (one DECT scan = two raw data sets) by passing them through a polynomial function. The polynomial's coefficients are determined using a general least squares fit based on thresholded images of a calibration phantom. The calibration phantom's dimension should be of the same order of magnitude as the test object, but other than that no assumptions on its exact size or positioning are made. Once the decomposition coefficients are determined DECT raw data can be decomposed by simply passing them through the polynomial. To demonstrate EDEC simulations of an oval CTDI phantom, a lung phantom, a thorax phantom and a mouse phantom were carried out. The method was further verified by measuring a physical mouse phantom, a half-and-half-cylinder phantom and a Yin-Yang phantom with a dedicated in vivo dual source micro-CT scanner. The raw data were decomposed into their components, reconstructed, and the pixel values obtained were compared to the theoretical values. The determination of the calibration coefficients with EDEC is very robust and depends only slightly on the type of calibration phantom used. The images of the test phantoms (simulations and measurements) show a nearly perfect agreement with the theoretical micro values and density values. Since EDEC is an empirical technique it inherently compensates for scatter components. The empirical dual energy calibration technique is a pragmatic, simple, and reliable calibration approach that produces highly quantitative DECT images.

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Year:  2007        PMID: 17926967     DOI: 10.1118/1.2769104

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  14 in total

1.  Geometric calibration for a dual tube/detector micro-CT system.

Authors:  Samuel M Johnston; G Allan Johnson; Cristian T Badea
Journal:  Med Phys       Date:  2008-05       Impact factor: 4.071

2.  Estimator for photon counting energy selective x-ray imaging with multibin pulse height analysis.

Authors:  Robert E Alvarez
Journal:  Med Phys       Date:  2011-05       Impact factor: 4.071

3.  Segmentation-free x-ray energy spectrum estimation for computed tomography using dual-energy material decomposition.

Authors:  Wei Zhao; Lei Xing; Qiude Zhang; Qingguo Xie; Tianye Niu
Journal:  J Med Imaging (Bellingham)       Date:  2017-06-30

4.  Experimental comparison of empirical material decomposition methods for spectral CT.

Authors:  Kevin C Zimmerman; Taly Gilat Schmidt
Journal:  Phys Med Biol       Date:  2015-03-27       Impact factor: 3.609

5.  Characterization and potential applications of a dual-layer flat-panel detector.

Authors:  Linxi Shi; Minghui Lu; N Robert Bennett; Edward Shapiro; Jin Zhang; Richard Colbeth; Josh Star-Lack; Adam S Wang
Journal:  Med Phys       Date:  2020-05-18       Impact factor: 4.071

6.  Construction of mouse phantoms from segmented CT scan data for radiation dosimetry studies.

Authors:  D Welch; A D Harken; G Randers-Pehrson; D J Brenner
Journal:  Phys Med Biol       Date:  2015-04-10       Impact factor: 3.609

7.  Prior image constrained scatter correction in cone-beam computed tomography image-guided radiation therapy.

Authors:  Stephen Brunner; Brian E Nett; Ranjini Tolakanahalli; Guang-Hong Chen
Journal:  Phys Med Biol       Date:  2011-01-21       Impact factor: 3.609

8.  Locally linear constraint based optimization model for material decomposition.

Authors:  Qian Wang; Yining Zhu; Hengyong Yu
Journal:  Phys Med Biol       Date:  2017-10-19       Impact factor: 3.609

9.  Photon counting spectral CT component analysis of coronary artery atherosclerotic plaque samples.

Authors:  L Boussel; P Coulon; A Thran; E Roessl; G Martens; M Sigovan; P Douek
Journal:  Br J Radiol       Date:  2014-05-29       Impact factor: 3.039

10.  Comparative Study of Dual Energy Cone-Beam CT using a Dual-Layer Detector and kVp Switching for Material Decomposition.

Authors:  Linxi Shi; N Robert Bennett; Edward Shapiro; Richard E Colbeth; Josh Star-Lack; Minghui Lu; Adam S Wang
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2020-03-16
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