&lt;title&gt;Characterization of an amorphous-silicon fluoroscopic imager&lt;/title&gt;

Colbeth, Richard E.; Allen, Maxwell J.; Day, D. J.; Gilblom, David L.; Klausmeier-Brown, M. E.; Pavkovich, John M.; Seppi, E.; Shapiro, Edward G.

doi:10.1117/12.274010

Cited by 10 publications

(9 citation statements)

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“…A great deal of effort has been devoted to the research and development of digital x-ray flat-panel imagers ͑FPIs͒ in the past years, [1][2][3][4][5][6][7][8][9][10] and several are commercially available at present. Since their advent, the x-ray imaging community has been investigating the application of the x-ray FPIs in digital radiography ͑DR͒ and digital fluoroscopy ͑DF͒, and some encouraging results have already been reported.…”

Section: Introductionmentioning

confidence: 99%

“…Since their advent, the x-ray imaging community has been investigating the application of the x-ray FPIs in digital radiography ͑DR͒ and digital fluoroscopy ͑DF͒, and some encouraging results have already been reported. 1,[4][5][6][7][8][9][10][11] Recently, the application of the x-ray FPI in cone beam volume CT ͑CBVCT͒ as a 2-D x-ray detector has increasingly drawn the attention of the CBVCT community, and a few preliminary and interesting results have been presented. [12][13][14][15][16][17][18][19][20] Based upon the technology of fabricating an array of hydrogenated amorphous silicon (a-Si:H) thin-film transistors ͑TFTs͒, the currently available x-ray FPIs can be basically categorized into two types.…”

Section: Introductionmentioning

confidence: 99%

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Cone beam volume CT image artifacts caused by defective cells in x‐ray flat panel imagers and the artifact removal using a wavelet‐analysis‐based algorithm

Tang

Ning

et al. 2001

Medical Physics

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The application of x-ray flat panel imagers (FPIs) in cone beam volume CT (CBVCT) has attracted increasing attention. However, due to a deficient semiconductor array manufacturing process, defective cells unavoidably exist in x-ray FPIs. These defective cells cause their corresponding image pixels in a projection image to behave abnormally in signal gray level, and result in severe streak and ring artifacts in a CBVCT image reconstructed from the projection images. Since a three-dimensional (3-D) back-projection is involved in CBVCT, the formation of the streak and ring artifacts is different from that in the two-dimensional (2-D) fan beam CT. In this paper, a geometric analysis of the abnormality propagation in the 3D back-projection is presented, and the morphology of the streak and ring artifacts caused by the abnormality propagation is investigated through both computer simulation and phantom studies. In order to calibrate those artifacts, a 2D wavelet-analysis-based statistical approach to correct the abnormal pixels is proposed. The approach consists of three steps: (1) the location-invariant defective cells in an x-ray FPI are recognized by applying 2-D wavelet analysis on flat-field images, and a comprehensive defective cell template is acquired; (2) based upon the template, the abnormal signal gray level of the projection image pixels corresponding to the location-invariant defective cells is replaced with the interpolation of that of their normal neighbor pixels; (3) that corresponding to the isolated location-variant defective cells are corrected using a narrow-windowed median filter. The CBVCT images of a CT low-contrast phantom are employed to evaluate this proposed approach, showing that the streak and ring artifacts can be reliably eliminated. The novelty and merit of the approach are the incorporation of the wavelet analysis whose intrinsic multi-resolution analysis and localizability make the recognition algorithm robust under variable x-ray exposure levels between 30% and 70% of the dynamic range of an x-ray FPI.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cone beam volume CT image artifacts caused by defective cells in x‐ray flat panel imagers and the artifact removal using a wavelet‐analysis‐based algorithm

Tang

Ning

et al. 2001

Medical Physics

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“…The results reported herein represent a continuation of that previous work, but based upon a solid-state, flatpanel dynamic digital X-ray image detector (FDXD), rather than an image intensifier. Other groups are developing similar dynamic acquisition devices [3,4,5], but we believe we were the first to report clinical results [6,9]. In this paper we briefly present the results of the technical evaluation, and then describe our clinical experience to date.…”

Section: Introductionmentioning

confidence: 97%

Initial technical and clinical evaluation of a new universal image receptor system

et al. 2000

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The aim of this study was to evaluate the physical performance of an experimental flat-panel digital X-ray detector plate (FDXD), and to assess its clinical potential in radiographic and fluoroscopic mode. The efficiency of the detector was assessed by calculating the low-frequency detective quantum efficiency (DQE(0)), and a measure of image quality was obtained using a threshold contrast detail detectability (TCDD) test object. A range of clinical examinations were also carried out, and the results reviewed by members of the radiology staff. The DQE(0) of the system was calculated to be almost 75%, compared with a value of approximately 20 % for modern computed radiography equipment, offering the potential for increased image quality or significant dose reduction. Measurements using the TCDD test object demonstrated a corresponding advantage for the FDXD in image quality and dose efficiency. Clinical studies are producing radiographic results which are at least the equal of the best currently available digital technology, and a limited number of examinations using fluoroscopic mode at 25 frames per second have been equally encouraging. Equipment using FDXD technology could potentially fulfill all the radiographic and fluoroscopic requirements of the digital department, with improved image quality and dose efficiency.

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“…These three physical characteristics are the Noise Power Spectrum (NPS), Modulation Transfer Function (MTF) and the Detective Quantum Efficiency (DQE). Different methods of computing the NPS, MTF and DQE has been investigated and used in the literature [2][3][4][5][6][7][8][9][10][11][12][13][14]16,[20][21][22][23][24][25][26][27][28]30]. The methods utilized here are described in the next section.…”

Section: Introductionmentioning

confidence: 99%

Measurements of the Modulation Transfer Function, Normalized Noise Power Spectrum and Detective Quantum Efficiency for two flat panel detectors: A Fluoroscopic and a Cone Beam Computer Tomography Flat Panel Detectors

Benítez

Ning

Conover

et al. 2009

Journal of X-Ray Science and Technology

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The physical performance of two Flat Panel Detectors has been evaluated. The first Flat Panel Detector is for Fluoroscopic applications, Varian PaxScan 2520, and the second is for Cone Beam Computer Tomography applications, Varian PaxScan 4030CB. First, the spectrum of the X-ray source was measured. Second, the linearity of the detectors was investigated by using an ionization chamber and the average ADU values of the detectors. Third, the temporal resolution was characterized by evaluating their image lag. Fourth, their spatial resolution was characterized by the pre-sampling Modulation Transfer Function. Fifth, the Normalized Noise Power Spectrum was calculated for various exposures levels. Finally, the Detective Quantum Efficiency was obtained as a function of spatial frequency and entrance exposure. The results illustrate that the physical performance in Detective Quantum Efficiency and Normalized Noise Power Spectrum of the Cone Beam Computer Tomography detector is superior to that of the fluoroscopic detector whereas the latter detector has a higher spatial resolution as demonstrated by larger values of its Modulation Transfer Function at large spatial frequencies.

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<title>Characterization of an amorphous-silicon fluoroscopic imager</title>

Cited by 10 publications

References 0 publications

Cone beam volume CT image artifacts caused by defective cells in x‐ray flat panel imagers and the artifact removal using a wavelet‐analysis‐based algorithm

Cone beam volume CT image artifacts caused by defective cells in x‐ray flat panel imagers and the artifact removal using a wavelet‐analysis‐based algorithm

Initial technical and clinical evaluation of a new universal image receptor system

Measurements of the Modulation Transfer Function, Normalized Noise Power Spectrum and Detective Quantum Efficiency for two flat panel detectors: A Fluoroscopic and a Cone Beam Computer Tomography Flat Panel Detectors

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