Relevant bibliographies by topics / X-Ray Computed

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'X-Ray Computed'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "X-Ray Computed"

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Kalender, Willi A. "X-ray computed tomography." Physics in Medicine and Biology 51, no. 13 (June 20, 2006): R29—R43. http://dx.doi.org/10.1088/0031-9155/51/13/r03.

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Phillips,, D. H., and J. J. Lannutti. "X-ray computed tomography." NDT & E International 27, no. 2 (April 1994): 101. http://dx.doi.org/10.1016/0963-8695(94)90323-9.

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Michael, Greg. "X-ray computed tomography." Physics Education 36, no. 6 (October 19, 2001): 442–51. http://dx.doi.org/10.1088/0031-9120/36/6/301.

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Bonnet, S., A. Koenig, S. Roux, P. Hugonnard, R. Guillemaud, and P. Grangeat. "Dynamic X-ray computed tomography." Proceedings of the IEEE 91, no. 10 (October 2003): 1574–87. http://dx.doi.org/10.1109/jproc.2003.817868.

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Baird, Emily, and Gavin Taylor. "X-ray micro computed-tomography." Current Biology 27, no. 8 (April 2017): R289—R291. http://dx.doi.org/10.1016/j.cub.2017.01.066.

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Dubsky, S., R. A. Jamison, S. C. Irvine, K. K. W. Siu, K. Hourigan, and A. Fouras. "Computed tomographic x-ray velocimetry." Applied Physics Letters 96, no. 2 (January 11, 2010): 023702. http://dx.doi.org/10.1063/1.3285173.

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Harding, G., J. Kosanetzky, and U. Neitzel. "X-ray diffraction computed tomography." Medical Physics 14, no. 4 (July 1987): 515–25. http://dx.doi.org/10.1118/1.596063.

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Buynak, C. F., and R. H. Bossi. "Applied X-ray computed tomography." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 99, no. 1-4 (May 1995): 772–74. http://dx.doi.org/10.1016/0168-583x(94)00615-6.

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Zhang, Wei, Dianwen Zhu, Michael Lun, and Changqing Li. "Collimated superfine x-ray beam based x-ray luminescence computed tomography." Journal of X-Ray Science and Technology 25, no. 6 (November 28, 2017): 945–57. http://dx.doi.org/10.3233/xst-17265.

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Zhang, Wei, Michael C. Lun, Alex Anh-Tu Nguyen, and Changqing Li. "X-ray luminescence computed tomography using a focused x-ray beam." Journal of Biomedical Optics 22, no. 11 (November 10, 2017): 1. http://dx.doi.org/10.1117/1.jbo.22.11.116004.

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Dissertations / Theses on the topic "X-Ray Computed"

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Moore, Jared William. "Adaptive X-ray Computed Tomography." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145396.

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An adaptive pre-clinical x-ray computed tomography system, named "FaCT" was designed, built, and tested at the University of Arizona's Center for Gamma-Ray Imaging (CGRI). The FaCT system possesses the unique ability to change its magnification and dynamically mask the x-ray beam profile. Using these two abilities, the FaCT system can adapt its configuration to the object being imaged, and the task being performed, while achieving a reduction in the radiation dose applied for imaging.Development of the system included the design of all mechanical components, motion systems, and safety systems. It also included system integration of all electronics, motors, and communication channels. Control software was developed for the system and several high-performance reconstruction algorithms were implemented on graphics processing units for reconstructing tomographic data sets acquired by the system. A new geometrical calibration method was developed for calibrating the system that makes use of the full image data gathered by the system and does not rely on markers.An adaptive imaging procedure consisting of a preliminary scout scan, human guidance, and a diagnostic quality scan was developed for imaging small volumes of interest in the interior of an object at substantially reduced dose. The adaptive imaging procedure makes use of FaCT's adjustable magnification, beam-masking capability, and high-performance reconstruction software to achieve high-quality reconstruction of a volume of interest with less dose than would be required by a traditional x-ray computed tomography system without adaptive capabilities.To address ongoing research into mathematical rules for adapting an imaging system, such as FaCT, to better perform a given estimation task, a method of quantifying a system's ability to estimate a parameter of interest in the presence of nuisance parameters based on the Fisher Information was proposed. The method requires a statistical model of object variability. Possible strategies for increasing the performance of an estimation task, given an adaptive system, were suggested.
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Halverson, Clinton. "Characterization of geomaterials with X-ray computed tomography (X-ray CT)." [Ames, Iowa : Iowa State University], 2008.

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Qiu, Wei. "Iterative algorithms for volumetric X-ray computed tomography." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.571870.

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Cone beam computed tomography (CBCT) enables a volumetric image reconstruction from a set of 2D projection data. This thesis studies the performance of a wide range iterative algorithms in various aspects, aiming to generate a better CBCT image reconstruction, especially when projection data is limited. We have implemented a wide range of algebraic iterative algorithms. Hence, the performance of ART, SART and OS-SART is studied based on a range of image quality measures. The major limitations of traditional iterative methods are their computational time. The conjugate gradients (CG) algorithm and its variants can be used to solve linear systems of equations arising from CBCT. Their applications can be found in a general linear algebra context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this final part of the thesis, to overcome this diculty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization has been developed in this framework, and can produce significant improvement in the reconstructed images for limited data case.
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Eck, Brendan Lee. "Myocardial Perfusion Imaging with X-Ray Computed Tomography." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1525187076597075.

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Stirrup, James Elliott. "Mycardial applications of cardiovascular X-ray computed tomography." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/18969.

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This thesis evaluated the role of cardiovascular computed tomography (CCT) in assessing the left ventricular (LV) myocardium. The technical and clinical performance of single-slice CT for attenuation correction (CTAC) of SPECT myocardial perfusion scintigraphy (MPS) was evaluated. Early and delayed multi-slice CT (eCCT and dCCT respectively) myocardial enhancement patterns were validated against SPECT MPS (single-source CCT) and cardiovascular magnetic resonance imaging (CMR, dual-source CCT) for detection of chronic myocardial infarction (MI), as were CCT measures of segmental LV wall thickness and global and regional LV function. Impact of cardiac phase and reconstruction kernel on agreement with SPECT MPS was also measured. The following results were shown: CTAC showed no benefits on MPS report or reporter confidence when studied in a way that reflects clinical practice; dCCT best identifies segmental MI, showing good agreement and high specificity, negative predictive value and accuracy compared with SPECT MPS and CMR; choice of smooth or medium-smooth reconstruction kernel appears relatively unimportant; dual-energy dCCT may be more sensitive for segmental MI on CMR; CCT end-systolic wall thickness is a better predictor of myocardial scarring on MPS and CMR than end-diastolic wall thickness; CCT overestimates end-systolic and end-diastolic volumes on MPS but LV ejection fraction is equivalent; CCT shows no systematic differences in measures of global LV function when compared to CMR; measures of regional ventricular function on CCT show excellent and good agreement with MPS and CMR respectively; inter- and intraobserver agreement for dCCT myocardial enhancement patterns and regional LV function is excellent.
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Ghous, Abid Petroleum Engineering Faculty of Engineering UNSW. "Digital formation evaluation via x-ray micro-computed tomography." Awarded by:University of New South Wales. School of Petroleum Engineering, 2005. http://handle.unsw.edu.au/1959.4/20581.

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Machined fragments of 10 core plugs from oshore reservoirs have been analysed using a high resolution X-ray micro-computed tomography (micro-CT) facility. The facility includes a system capable of acquiring 3D images made up of 20003 voxels on core plugs up to 6 cm diameter with resolutions down to 2 um. The cores analysed include six cores from a gas reservoir and four cores from an oil reservoir. The cores exhibit a very broad range of pore and grain sizes, porosity, permeability and mineralogy. The petrological data, available only for gas reservoir cores, is compared with the data obtained from the tomographic images. Computational results made directly on the digitized tomographic images are presented for the permeability, formation factor, resistivity index and drainage capillary pressure across a range of . We show that data over a range of porosity can be computed from a single fragment. We compare the computations of petrophysical data on fragments to conventional laboratory measurements on the full plug. Permeability predictions from digital and conventional core analysis are consistent. It is shown that a characteristic length scale can be dened as a quality control parameter for the estimation of permeability. Results for formation factor, drainage capillary pressure and resistivity index are encouraging. The results demonstrate the potential to predict petrophysical properties from core material not suited for laboratory testing (e.g., sidewall or damaged core and drill cuttings) and the feasibility of combining digitized images with numerical calculations to predict properties and derive correlations for specic rock lithologies. The small sample size required for analysis makes it possible to produce multiple measurements on a single plug. This represents a potential multiplier on the quantity of core data allowing meaningful distributions or spreads in petrophysical properties to be estimated. We discuss the current limitations of the methodology and suggest improvements; in particular the need to calibrate the simulated data to parallel laboratory core measurements. We also describe the potential to extend the methodology to a wider range of petrophysical properties. This development could lead to a more systematic study of the assumptions, interpretations and analysis methods commonly applied within industry and lead to better correlations between petrophysical properties and log measurements.
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Nielsen, Brent Daniel. "Non-Destructive Soil Testing Using X-Ray Computed Tomography." Thesis, Montana State University, 2004. http://etd.lib.montana.edu/etd/2004/nielsen/NielsenB1204.pdf.

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The mechanical behavior of soils is highly dependent on the particle microstructure. Traditional geotechnical engineering soil tests generally do not measure soil properties on a micro-scale; instead, macro scale properties are commonly used as estimates of microstructure properties in determining soil engineering behavior. Additionally, traditional geotechnical engineering soil tests are destructive in nature, and many test methods destroy the same soil properties they intend to measure. The goal of this research was to develop non-destructive soil test methods using x-ray computer-aided tomography (CT) scanning techniques to determine soil index properties. The CT scanning process provides a promising method for examining soil microstructure in a non-destructive manner. This research had two main objectives. The first was to configure the Montana State University Civil Engineering Department\'s computer-aided tomography scanner to perform CT scans on soil samples. The second objective was to use the CT scanner to develop nondestructive test procedures to determine geotechnical index properties of soils. Test methods were developed in this study to determine porosity, grain size distribution, and pore size distribution. The results from the first objective showed that the MSU CT scanning equipment is capable of producing high quality CT scans of soil materials. Resolution limitations of the scanner define the smallest soil grain size that is detectable in a CT scan, but the scan resolution may be improved by using smaller sample sizes for small particle soils. The results of the second portion of the study show that the non-destructive CT scanning test methods compare favorably with traditional geotechnical laboratory mechanical test methods. CT-measured porosity values and grain size distributions compared well with mechanical testing results, which were used to validate the new test methods. In addition, the CT-measured pore size distributions were in good agreement with an accepted pore size mathematical model. Since traditional pore size distribution tests are time-consuming, labor intensive, and destructive in nature, the non-destructive x-ray CT scanning test methods developed in this study show strong promise as a means for measuring an elusive soil property that cannot be accurately measured using traditional geotechnical testing procedures.
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Lotz, Jeffrey Charles. "Hip fracture risk predictions by x-ray computed tomography." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14410.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Harvard-MIT Division of Health Sciences and Technology Program in Medical Engineering and Medical Physics, 1988.
Includes bibliographical references.
by Jeffrey Charles Lotz.
Ph.D.
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Mishra, Sourav. "Collimator width Optimization in X-ray Luminescent Computed Tomography." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/51118.

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X-ray Luminescent Computed Tomography (XLCT) is a new imaging modality which is under extensive trials at present. The modality works by selective excitation of X-ray sensitive nanophosphors and detecting the optical signal thus generated. This system can be used towards recreating high quality tomographic slices even with low X-ray dose. There have been many studies which have reported successful validation of the underlying philosophy. However, there is still lack of information about optimal settings or combination of imaging parameters, which could yield best outputs. Research groups participating in this area have reported results on basis of dose, signal to noise ratio or resolution only.
In this thesis, the candidate has evaluated XLCT taking into consideration noise and resolution in terms of composite indices. Simulations have been performed for various beam widths and noise & resolution metrics deduced. This information has been used in evaluating quality of images on basis of CT Figure of Merit & a modified Wang-Bovik Image Quality index. Simulations indicate the presence of an optimal setting which can be set prior to extensive scans. The conducted study, although focusing on a particular implementation, hopes to establish a paradigm in finding best settings for any XLCT system. Scanning with an optimal setting preconfigured can help in vastly reducing the cost and risks involved with this imaging modality.

Master of Science
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Ebert, Matthias. "Non-ideal projection data in X-ray computed tomography." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10605022.

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Books on the topic "X-Ray Computed"

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Carmignato, Simone, Wim Dewulf, and Richard Leach, eds. Industrial X-Ray Computed Tomography. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-59573-3.

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Cierniak, Robert. X-Ray Computed Tomography in Biomedical Engineering. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-027-4.

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Hsieh, Jiang. Computed tomography: Principles, design, artifacts, and recent advances. Bellingham, Washington: SPIE, 2015.

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T, Lee Joseph K., Sagel Stuart S. 1940-, and Stanley Robert J. 1937-, eds. Computed body tomography with MRI correlation. 2nd ed. New York: Raven Press, 1989.

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DeMaio, Daniel N. Registry review in computed tomography. Philadelphia: W.B. Saunders, 1996.

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K, Fishman Elliot, and Jeffrey R. Brooke, eds. Multidetector CT: Principles, techniques, and clinical applications. Philadelphia: Lippincott Williams & Wilkins, 2004.

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1934-, Tateno Yukio, Iinuma Takeshi 1933-, and Takano M. 1937-, eds. Computed radiography. Tokyo: Springer-Verlag, 1987.

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Alexander, Joachim. Computed tomography: Assessment criteria, CT system technology, clinical applications. Berlin: Siemens Aktiengesellschaft, 1986.

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Alexander, Joachim. Computed tomography: Assessment criteria, CT system technology, clinical applications. Germany: Siemans, 1986.

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F, Mees, and Geological Society of London, eds. Applications of X-ray computed tomography in the geosciences. London: The Geological Society, 2003.

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Book chapters on the topic "X-Ray Computed"

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Sakuma, Sadayuki, Toshihiko Takeuchi, and Takeo Ishigaki. "X-ray Computed Tomography." In Diagnostic Imaging of the Liver, Biliary Tract and Pancreas, 54–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-71307-1_4.

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El-Fishawy, Paul. "X-ray Computed Tomography." In Encyclopedia of Autism Spectrum Disorders, 3413. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_101594.

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Carmignato, Simone, Filippo Zanini, Markus Baier, and Elia Sbettega. "X-Ray Computed Tomography." In Precision Metal Additive Manufacturing, 313–46. First edition. | Boca Raton, FL : CRC Press, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429436543-12.

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Gibby, Wendell A. "X-Ray Computed Tomography." In Neuroimaging, 3–24. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1152-5_1.

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Jan, Jiří. "X-Ray Computed Tomography." In Medical Image Processing, Reconstruction and Analysis, 111–30. Other titles: Medical image processing, reconstruction, and restoration Description: Second edition. | Boca Raton: CRC Press, 2019. | Preceded by Medical image processing, reconstruction, and restoration/Jiří Jan.2006.: CRC Press, 2019. http://dx.doi.org/10.1201/b22391-6.

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Chityala, Ravishankar, and Sridevi Pudipeddi. "X-Ray and Computed Tomography." In Image Processing and Acquisition using Python, 277–313. Second edition. | Boca Raton : Chapman & Hall/CRC Press, 2020. | Series: Chapman & Hall/CRC the Python series: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9780429243370-13.

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King, Martin T., and Michael J. Zelefsky. "X-Ray and Computed Tomography." In Emerging Technologies in Brachytherapy, 233–42. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2017] | Series: Series in medical physics and biomedical engineering: CRC Press, 2017. http://dx.doi.org/10.1201/9781315120966-15.

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Knapp, R., I. Bangerl, and D. zur Nedden. "Electron beam computed tomography (EBCT)." In Advances in X-Ray Contrast, 67–80. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-3959-5_10.

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Molteni, Roberto. "X-Ray Imaging: Fundamentals of X-Ray." In Micro-computed Tomography (micro-CT) in Medicine and Engineering, 7–25. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16641-0_2.

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Joarde, Rita, and Neil Crundwell. "Computed Tomography: Technical Information." In Chest X-Ray in Clinical Practice, 167–84. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-099-9_16.

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Conference papers on the topic "X-Ray Computed"

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Yoshimura, Hideyuki, Chikara Miyata, Chiaki Kuzuryu, Ayumi Hori, Takashi Obi, and Nagaaki Ohyama. "X-ray computed tomography using projection x-ray microscope." In International Symposium on Optical Science and Technology, edited by Ulrich Bonse. SPIE, 2002. http://dx.doi.org/10.1117/12.452841.

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Dubsky, S., R. A. Jamison, S. C. Irvine, K. K. W. Siu, K. Hourigan, A. Fouras, and Karen K. W. Siu. "Computed Tomographic X-ray Velocimetry." In 6TH INTERNATIONAL CONFERENCE ON MEDICAL APPLICATIONS OF SYNCHROTRON RADIATION. AIP, 2010. http://dx.doi.org/10.1063/1.3478193.

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Dai, Xianjin, Kathyayini Sivasubramanian, and Lei Xing. "High spatial resolution x-ray luminescence computed tomography and x-ray fluorescence computed tomography." In Molecular-Guided Surgery: Molecules, Devices, and Applications V, edited by Brian W. Pogue and Sylvain Gioux. SPIE, 2019. http://dx.doi.org/10.1117/12.2511875.

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Lun, Michael, and Changqing Li. "Focused x-ray luminescence computed tomography." In Developments in X-Ray Tomography XII, edited by Bert Müller and Ge Wang. SPIE, 2019. http://dx.doi.org/10.1117/12.2532096.

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La Riviere, P. J., P. Vargas, G. Fu, and L. J. Meng. "Accelerating X-ray fluorescence computed tomography." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2009. http://dx.doi.org/10.1109/iembs.2009.5333568.

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Zhang, Wei, Dianwen Zhu, Kun Zhang, and Changqing Li. "Microscopic x-ray luminescence computed tomography." In SPIE BiOS, edited by Fred S. Azar and Xavier Intes. SPIE, 2015. http://dx.doi.org/10.1117/12.2076797.

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Oksuz, Ibrahim, Matt Bisbee, Nerine J. Cherepy, Andrew Townsend, James Hall, Joseph Nicolino, Saphon Hok, and Lei Cao. "Fast neutron computed tomography of multi-material complex objects." In Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XXIII, edited by Nerine J. Cherepy, Michael Fiederle, and Ralph B. James. SPIE, 2021. http://dx.doi.org/10.1117/12.2595862.

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Lun, Michael C., and Changqing Li. "High-resolution x-ray luminescence computed tomography." In Biomedical Applications in Molecular, Structural, and Functional Imaging, edited by Barjor S. Gimi and Andrzej Krol. SPIE, 2020. http://dx.doi.org/10.1117/12.2544493.

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Allegra, D., E. Ciliberto, P. Ciliberto, F. L. M. Milotta, G. Petrillo, F. Stanco, and C. Trombato. "Virtual unrolling using X-ray computed tomography." In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362908.

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Wei, Yuchuan, Hengyong Yu, Jiang Hsieh, and Ge Wang. "General formulation for X-ray computed tomography." In SPIE Optics + Photonics, edited by Ulrich Bonse. SPIE, 2006. http://dx.doi.org/10.1117/12.680745.

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Reports on the topic "X-Ray Computed"

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Winter, John M., Green Jr., and Jr Robert E. X-ray Computed Tomography of Ultralightweight Metals. Fort Belvoir, VA: Defense Technical Information Center, October 2001. http://dx.doi.org/10.21236/ada390635.

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Maylotte, D. H., C. L. Spiro, P. G. Kosky, and E. J. Lamby. X-ray Computed Tomography of coal: Final report. Office of Scientific and Technical Information (OSTI), December 1986. http://dx.doi.org/10.2172/6339446.

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Divin, C. J. AlignCT: Fine alignment for x-ray computed tomography systems. Office of Scientific and Technical Information (OSTI), February 2016. http://dx.doi.org/10.2172/1239195.

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Brown, W., K. Champley, S. Glenn, and H. Martz. X-ray Computed Tomography Imaging of Printed Circuit Boards. Office of Scientific and Technical Information (OSTI), January 2018. http://dx.doi.org/10.2172/1544975.

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Jackson, J. Wolter X-Ray Microscope Computed Tomography Ray-Trace Model with Preliminary Simulation Results. Office of Scientific and Technical Information (OSTI), February 2006. http://dx.doi.org/10.2172/883616.

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Smith, R. A., M. J. Paulus, J. M. Branning, and P. J. Phillips. X-Ray Computed Tomography on a Cellular Polysiloxane under Compression. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/769294.

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Young, Steven. Imaging APO-BMI with Micro X-ray Computed Tomography (CT). Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1772371.

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GRONDIN, Yannick, Claudio LOBOS, Pascal TURBERG, Aurèle PARRIAUX, and Reto MEULI. Quantitative analysis of rock fracture roughness with X-ray Computed Tomography. Cogeo@oeaw-giscience, September 2011. http://dx.doi.org/10.5242/iamg.2011.0090.

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Gaspard, Danièle, Benita Putlitz, and Lukas Baumgartner. X-ray Computed Tomography – A Promising Tool For Brachiopod Shell Investigations. Cogeo@oeaw-giscience, September 2011. http://dx.doi.org/10.5242/iamg.2011.0292.

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Choi, A., D. Miller, and D. Immel. DETERMINATION OF HLW GLASS MELT RATE USING X-RAY COMPUTED TOMOGRAPHY. Office of Scientific and Technical Information (OSTI), October 2011. http://dx.doi.org/10.2172/1027854.

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