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Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications
KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.ORCID iD: 0000-0002-5092-8822
KTH, School of Engineering Sciences (SCI), Physics.
KTH, School of Engineering Sciences (SCI), Physics.
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2015 (English)In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 2, no 3, 033502Article in journal (Refereed) PublishedText
Abstract [en]

Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2015. Vol. 2, no 3, 033502
Keyword [en]
silicon strip detector, photon-counting computed tomography, forward model, ring artifact, material decomposition
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:kth:diva-186578DOI: 10.1117/1.JMI.2.3.033502ISI: 000374234800003OAI: oai:DiVA.org:kth-186578DiVA: diva2:927983
Note

QC 20160513

Available from: 2016-05-13 Created: 2016-05-13 Last updated: 2016-09-08Bibliographically approved
In thesis
1. Characterization and Energy Calibration of a Silicon-Strip Detector for Photon-Counting Spectral Computed Tomography
Open this publication in new window or tab >>Characterization and Energy Calibration of a Silicon-Strip Detector for Photon-Counting Spectral Computed Tomography
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Multibin photon-counting x-ray detectors are promising candidates to be applied in next generation computed tomography (CT), whereby energy information from a broad x-ray spectrum can be extracted and properly used for improving image quality and correspondingly reducing radiation dose. A silicon-strip detector has been developed for spectral CT, which operates in photon-counting mode and allows pulse-height discrimination with 8 adjustable energy bins.

Critical characteristics, energy resolution and count-rate performance, of the detector are evaluated. An absolute energy resolution (E) from 1.5 keV to 1.9 keV with increasing x-ray energy from 40 keV to 120 keV is found. Pulse pileup degrades the energy resolution by 0.4 keV when increasing the input count rate from zero to 100 Mcps mm−2, while charge sharing shows negligible effect. A near linear relationship between the input and output count rates is observed up to 90 Mcps mm−2 in a clinical CT environment. In addition, no saturation effect appears for the maximally achieved photon flux of 485 Mphotons s−1 mm−2 with a count rate loss of 30%.

The detector is energy calibrated in terms of gain and offset with the aid of monoenergetic x rays. The gain variation among channels is below 4%, whereas the variation of offsets is on the order of 1 keV. In order to do the energy calibration in a routinely available way, a method that makes use of the broad x-ray spectrum instead of using monoenergetic x rays is proposed. It is based on a regression analysis that adjusts a modelled spectrum of deposited energies to a measured pulse-height spectrum. Application of this method shows high potential to be applied in an existing CT scanner with an uncertainty of a calibrated threshold between 0.1 and 0.2 keV.

The energy-calibration method is further used in the development of a spectral response model of the detector. This model is used to accurately bin-wise predict the response of each detector channel, which is validated by two application examples. First, the model is used in combination with the inhomogeneity compensation method to eliminate ring artefacts in CT images. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. Additionally, the contrast agent concentrations are reconstructed with more than 94% accuracy.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2016. 46 p.
Series
TRITA-FYS, ISSN 0280-316X ; 2016:56
National Category
Medical Equipment Engineering
Research subject
Medical Technology
Identifiers
urn:nbn:se:kth:diva-192240 (URN)978-91-7729-079-7 (ISBN)
External cooperation:
Public defence
2016-09-30, Kollegiesalen, Brinellvägen 8, KTH, Stockholm, 09:00 (English)
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Supervisors
Note

QC 20160908

Available from: 2016-09-08 Created: 2016-09-08 Last updated: 2016-09-09Bibliographically approved

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