The DOI matches its Crossref record.
A Method for Correcting Bone Induced Artifacts in Computed Tomography Scanners
Abstract
A method that corrects for artifacts in X-ray transmission scanners created by the alteration of the energy spectrum by bone is described. The method involves two reconstructions of the pictures: the first establishes the approximate distribution of bone and the second enables the artifacts to be eliminated. The first reconstruction is needed to establish the total amount of bone along each ray. Assuming that the X-ray energy spectrum is known, it is shown how the line integrals can be corrected. The method was tested on several mathematical phantoms as well as on human head data. The nonlinear nature of the spectral artifacts is shown to produce streaks in certain phantoms.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“the large extracranial metal components and dental cement of the implant can cause beam hardening that can appear as cupping, streaks, dark bands or flare in the µCT38–40.”
From Oxytocin neurons enable social transmission of maternal behaviour (2021) · cites this paper as [40]
Citations
Cited by
Sorted by citations
CT artifacts: causes and reduction techniques
Boas, F. E., & Fleischmann, D. (2012) · Imaging in Medicine · doi:10.2217/iim.12.13 · Cited by 850
“This can be addressed using iterative reconstruction [12, 13].”
BackgroundStatistical image reconstruction for polyenergetic X-ray computed tomography
Elbakri, I. A., & Fessler, J. A. (2002) · IEEE Transactions on Medical Imaging · doi:10.1109/42.993128 · Cited by 693
“These classes can be determined by segmenting a FBP reconstruction that has been “corrected” for beam hardening effects [18].”
BackgroundMethodResultInfluentialX-ray-based attenuation correction for positron emission tomography/computed tomography scanners
Kinahan, P. E., Hasegawa, B. H., & Beyer, T. (2003) · Seminars in Nuclear Medicine · doi:10.1053/snuc.2003.127307 · Cited by 515
Assessment of abdominal fat content by computed tomography
Borkan, G. A., Gerzof, S. G., Robbins, A. H., Hults, D. E., Silbert, C. K., & Silbert, J. E. (1982) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/36.1.172 · Cited by 491
An iterative maximum-likelihood polychromatic algorithm for CT
Man, B. D., Nuyts, J. L., Dupont, P. J., et al. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.959297 · Cited by 431
“All other methods [ 18 ]‐[26] are either limited to two or three substances, or apply some extra approximations because of limited computational power at the time they were invented.”
BackgroundMethodAn Improved Algorithm for Reprojecting Rays through Pixel Images
Joseph, P. M. (1982) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1982.4307572 · Cited by 378
Self-citationMetal streak artifacts in X-ray computed tomography: a simulation study
Man, B. D., Nuyts, J. L., Dupont, P. J., et al. (1999) · IEEE Transactions on Nuclear Science · doi:10.1109/23.775600 · Cited by 317
An iterative approach to the beam hardening correction in cone beam CT
Hsieh, J., Molthen, R. C., DAWSON, C. A., et al. (2000) · Medical Physics · doi:10.1118/1.598853 · Cited by 281
“To overcome these difficulties, an iterative method was proposed to estimate and correct for the projection error in the reconstructed images [4].”
MethodAlgebraic reconstruction in CT from limited views
Andersen, A. H. (1989) · IEEE Transactions on Medical Imaging · doi:10.1109/42.20361 · Cited by 279
Oxytocin neurons enable social transmission of maternal behaviour
Carcea, I., Caraballo, N. L., Marlin, B. J., Ooyama, R., Riceberg, J. S., Mendoza Navarro, J. M., Opendak, M., Diaz, V. E., Schuster, L., Alvarado Torres, M. I., et al. (2021) · Nature · doi:10.1038/s41586-021-03814-7 · Cited by 268
Computerized tomography with X-ray, emission, and ultrasound sources
Kak, A. C. (1979) · Proceedings of the IEEE · doi:10.1109/proc.1979.11440 · Cited by 267
X-ray CT metal artifact reduction using wavelets: an application for imaging total hip prostheses
Zhao, S., Robeltson, D. D., Wang, G., et al. (2000) · IEEE Transactions on Medical Imaging · doi:10.1109/42.897816 · Cited by 246
Statistical Image Reconstruction Methods for Transmission Tomography
Fessler, J. A. (2010) · SPIE eBooks · doi:10.1117/3.831079.ch1 · Cited by 240
X-ray computed tomography: from medical imaging to dimensional metrology
Villarraga-Gómez, H., Herazo, E. L., & Smith, S. T. (2019) · Precision Engineering · doi:10.1016/j.precisioneng.2019.06.007 · Cited by 237
Modelling the physics in the iterative reconstruction for transmission computed tomography
Nuyts, J. L., Man, B. D., Fessler, J. A., Zbijewski, W. B., & Beekman, F. J. (2013) · Physics in Medicine and Biology · doi:10.1088/0031-9155/58/12/r63 · Cited by 199
“Based on these ideas, numerous correction methods for analytical reconstruction have been proposed (Joseph and Spital 1978, Herman 1979, Herman and Trivedi 1983, Joseph and Ruth 1997, Hsieh et al 2000, Yan et al 2000, Kyriakou et al 2010, Liu et al 2009).”
MethodMeganck, J. A., Kozloff, K. M., Thornton, M. M., et al. (2009) · Bone · doi:10.1016/j.bone.2009.07.078 · Cited by 186
“Reconstruction based approaches to prevent beam hardening artifacts in the 3D image can also be used in both dual-energy and single-energy imaging if the input spectrum is known [14], or may require a thresholding step so that path lengths can be estimated [11,15,16].”
Compensating for heterogeneities in proton radiation therapy
Urie, M. M., Goitein, M., & Wagner, M. (1984) · Physics in Medicine and Biology · doi:10.1088/0031-9155/29/5/008 · Cited by 183
Empirical beam hardening correction (EBHC) for CT
Kyriakou, Y., Meyer, E., Prell, D., et al. (2010) · Medical Physics · doi:10.1118/1.3477088 · Cited by 171
Blankespoor, S. C., Xu, X., Kaiki, K., Brown, J. K., Tang, H. R., Cann, C. E., & Hasegawa, B. H. (1996) · IEEE Transactions on Nuclear Science · doi:10.1109/23.531891 · Cited by 170
Jin, P., Bouman, C. A., & Sauer, K. D. (2015) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2015.2461492 · Cited by 165
“Alternatively, iterative post-processing techniques are lso widely used when the object being scanned is composed of two known materials that can be easily segmented [13]–[17].”
MethodLes, C. M., Keyak, J. H., Stover, S. M., Taylor, K., & Kaneps, A. J. (1994) · Journal of Orthopaedic Research® · doi:10.1002/jor.1100120610 · Cited by 150
O’Connor, M. K., & KEMP, B. J. (2006) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2006.05.005 · Cited by 149
Empirical cupping correction: A first‐order raw data precorrection for cone‐beam computed tomography
Kachelrieß, M., Sourbelle, K., & Kalender, W. A. (2006) · Medical Physics · doi:10.1118/1.2188076 · Cited by 145
Iterative correction of beam hardening artifacts in CT
Gompel, G. V., Slambrouck, K. V., Defrise, M., et al. (2011) · Medical Physics · doi:10.1118/1.3577758 · Cited by 144
Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction
Yan, C. H., Whalen, R. T., Beaupré, G. S., et al. (2000) · IEEE Transactions on Medical Imaging · doi:10.1109/42.832955 · Cited by 144
“Two most commonly used techniques are the water and bone corrections [ 10 ], [13] which assume that the materials in the scan field are either water or dense bone equivalent in X-ray attenuation characteristics.”
BackgroundMethodInfluentialElbakri, I. A., & Fessler, J. A. (2003) · Physics in Medicine and Biology · doi:10.1088/0031-9155/48/15/314 · Cited by 137
Fast iterative algorithm for metal artifact reduction in X-ray CT
Wang, G., Frei, T., & Vannier, M. W. (2000) · Academic Radiology · doi:10.1016/s1076-6332(00)80576-0 · Cited by 127
Kitagawa, K., George, R. T., Arbab‐Zadeh, A., et al. (2010) · Radiology · doi:10.1148/radiol.10091399 · Cited by 126
Zhang, R., Thibault, J., Bouman, C. A., et al. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2282370 · Cited by 124
High-Definition CT Gemstone Spectral Imaging of the Brain
Lin, X. Z., Miao, F., Li, J. Y., et al. (2011) · Journal of Computer Assisted Tomography · doi:10.1097/rct.0b013e3182058d5c · Cited by 124
CONRAD—A software framework for cone‐beam imaging in radiology
Maier, A., Hofmann, H. G., Berger, M., Fischer, P., Schwemmer, C., Wu, H., Mueller, K., Joachim Hornegger, A., Choi, J., Rieß, C., et al. (2013) · Medical Physics · doi:10.1118/1.4824926 · Cited by 119
A Framework for Spectral Artifact Corrections in X-Ray CT
Stonestrom, J. P., Alvarez, R. E., & Macovski, A. (1981) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1981.324786 · Cited by 114
The exponential edge-gradient effect in X-ray computed tomography
Joseph, P. M., & Spital, R. D. (1981) · Physics in Medicine and Biology · doi:10.1088/0031-9155/26/3/010 · Cited by 113
Self-citationJoseph, P. M., & Ruth, C. (1997) · Medical Physics · doi:10.1118/1.597970 · Cited by 111
Self-citationPost-reconstruction method for beam hardening in computerised tomography
Nalcioglu, O., & Lou, R. (1979) · Physics in Medicine and Biology · doi:10.1088/0031-9155/24/2/009 · Cited by 102
Maximum-likelihood dual-energy tomographic image reconstruction
Fessler, J. A., Elbakri, I. A., Sukovic, P., et al. (2002) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.467189 · Cited by 99
Application of Polychromatic µCT for Mineral Density Determination
Zou, W. P., Hunter, N., & Swain, M. V. (2010) · Journal of Dental Research · doi:10.1177/0022034510378429 · Cited by 94
“Beam hardening also results in artifacts that appear as cupping, streaks, dark bands, or flare artifacts (Duerinckx and Macovski, 1978; Joseph and Spital, 1978; Barrett and Keat, 2004).”
BackgroundWilliamson, J. F., Whiting, B. R., Benac, J., Murphy, R. J., Blaine, G. J., O’Sullivan, J. A., Politte, D. G., & Snyder, D. L. (2002) · Medical Physics · doi:10.1118/1.1509443 · Cited by 93
Characterization and correction of cupping effect artefacts in cone beam CT
Hunter, A., & McDavid, W. (2012) · Dentomaxillofacial Radiology · doi:10.1259/dmfr/19015946 · Cited by 88
A beam-hardening correction using dual-energy computed tomography
Coleman, A. J., & Sinclair, M. (1985) · Physics in Medicine and Biology · doi:10.1088/0031-9155/30/11/007 · Cited by 87
High-fidelity artifact correction for cone-beam CT imaging of the brain
Sisniega, A., Zbijewski, W. B., Xu, J., et al. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/4/1415 · Cited by 84
The feasibility of a piecewise‐linear dynamic bowtie filter
Hsieh, S. S., & Pelc, N. J. (2013) · Medical Physics · doi:10.1118/1.4789630 · Cited by 79
A model-based correction method for beam hardening artefacts in X-ray microtomography
de Casteele, E. V., Dyck, D. V., Sijbers, J., et al. (2004) · Journal of X-Ray Science and Technology · doi:10.3233/xst-2004-00100 · Cited by 78
“For systems consisting of more than two components, this method is often used in combination with the projection data and a first reconstruction image to obtain more prior information about the object under investigation [7,9,10].”
Normalized Metal Artifact Reduction in Head and Neck Computed Tomography
Lell, M., Meyer, E., Kuefner, M. A., May, M. S., Raupach, R., Uder, M., & Kachelrieß, M. (2012) · Investigative Radiology · doi:10.1097/rli.0b013e3182532f17 · Cited by 76
Bueno, M. R., Estrela, C., de Figueiredo, J. A. P., et al. (2010) · Journal of Endodontics · doi:10.1016/j.joen.2010.08.006 · Cited by 71
3D Imaging with Flat-Detector C-Arm Systems
Strobel, N. K., Meissner, O. A., Boese, J. M., Brunner, T. M., Heigl, B., Hoheisel, M., Lauritsch, G., Nagel, M., Pfister, M., Rührnschopf, E., et al. (2008) · Medical radiology · doi:10.1007/978-3-540-33125-4_3 · Cited by 70
A Comparative Study of Two Postreconstruction Beam Hardening Correction Methods
Herman, G. T., & Trivedi, S. S. (1983) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1983.4307626 · Cited by 70
Brabant, L., Pauwels, E., Dierick, M., et al. (2012) · NDT & E International · doi:10.1016/j.ndteint.2012.07.002 · Cited by 70
Cai, C., Rodet, T., Legoupil, S., et al. (2013) · Medical Physics · doi:10.1118/1.4820478 · Cited by 69
Single– versus Multi–Detector Row CT of the Brain: Quality Assessment
Jones, T. R., Kaplan, R. T., Lane, B., et al. (2001) · Radiology · doi:10.1148/radiology.219.3.r01jn47750 · Cited by 62
Specimen size and porosity can introduce error into μCT-based tissue mineral density measurements
Fajardo, R. J., Cory, E., Patel, N., et al. (2008) · Bone · doi:10.1016/j.bone.2008.08.118 · Cited by 61
Advances in the metrological traceability and performance of X-ray computed tomography
Dewulf, W., Bosse, H., Carmignato, S., et al. (2022) · CIRP Annals · doi:10.1016/j.cirp.2022.05.001 · Cited by 60
High‐resolution computed tomography for the comparative study of fossil and extant bone
Tate, J. R., & Cann, C. E. (1982) · American Journal of Physical Anthropology · doi:10.1002/ajpa.1330580108 · Cited by 59
Segmentation of artifacts and anatomy in CT metal artifact reduction
Karimi, S., Cosman, P. C., Wald, C., et al. (2012) · Medical Physics · doi:10.1118/1.4749931 · Cited by 58
Discretization of the radon transform and of its inverse by spline convolutions
Horbelt, S., Liebling, M., & Unser, M. A. (2002) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2002.1000260 · Cited by 57
“Re-projection is also used explicitly for beam-hardening correction [6], streak suppression [7], and the removal of artifacts caused by the presence of radio-opaque material such as metallic implants [8].”
BackgroundCerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging
Mormina, E., Petracca, M., Bommarito, G., Piaggio, N., Cocozza, S., & Inglese, M. (2017) · World Journal of Radiology · doi:10.4329/wjr.v9.i10.371 · Cited by 56
Remeysen, K., & Swennen, R. (2005) · International Journal of Coal Geology · doi:10.1016/j.coal.2005.10.001 · Cited by 55
Evans, J. D., Politte, D. G., Whiting, B. R., et al. (2011) · Medical Physics · doi:10.1118/1.3549757 · Cited by 54
Beam hardening correction in CT myocardial perfusion measurement
So, A., Hsieh, J., Li, J., et al. (2009) · Physics in Medicine and Biology · doi:10.1088/0031-9155/54/10/005 · Cited by 53
Statistical Image Reconstruction for Inconsistent CT Projection Data
Oehler, M., & Buzug, T. M. (2007) · Methods of Information in Medicine · doi:10.1160/me9041 · Cited by 51
CT image correction for beam hardening using simulated projection data
Meagher, J. M., Mote, C. D., & Skinner, H. B. (1990) · IEEE Transactions on Nuclear Science · doi:10.1109/23.55865 · Cited by 46
Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners
Abella, M., Vaquero, J. J., Sisniega, A., et al. (2011) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2011.06.008 · Cited by 45
“[21] P.M. Joseph, R.D. Spital, A method for correcting bone induced artifacts in computed tomography scanners, J. Comput.”
BackgroundInfluentialReduction of Beam-Hardening Artifacts in X-Ray CT
Menvielle, N., Goussard, Y., Orban, D., et al. (2005) · doi:10.1109/iembs.2005.1616814 · Cited by 44
“Postprocessing techniques [6], [7] involve an initial image, a segmentation and a correction.”
Lo, S.-C. B. (1988) · IEEE Transactions on Medical Imaging · doi:10.1109/42.14519 · Cited by 43
Estimation of a photon energy spectrum for a computed tomography scanner
Ruth, C., & Joseph, P. M. (1997) · Medical Physics · doi:10.1118/1.598159 · Cited by 43
Self-citationLocus coeruleus activity improves cochlear implant performance
Glennon, E., Valtcheva, S., Zhu, A., Wadghiri, Y. Z., Svirsky, M. A., & Froemke, R. C. (2022) · Nature · doi:10.1038/s41586-022-05554-8 · Cited by 45
Metal streak artifacts in X-ray computed tomography: a simulation study
Man, B. D., Nuyts, J. L., Dupont, P. J., et al. (2002) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.1998.773898 · Cited by 42
Boag, A., Bresler, Y., & Michielssen, E. (2000) · IEEE Transactions on Image Processing · doi:10.1109/83.862638 · Cited by 42
Segmentation‐free empirical beam hardening correction for CT
Schüller, S., Sawall, S., Stannigel, K., et al. (2015) · Medical Physics · doi:10.1118/1.4903281 · Cited by 40
Tang, X., Krupinski, E. A., Xie, H., & Stillman, A. E. (2018) · Medical Physics · doi:10.1002/mp.13095 · Cited by 39
Prior-Guided Metal Artifact Reduction for Iterative X-Ray Computed Tomography
Chang, Z., Ye, D. H., Srivastava, S., et al. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2886701 · Cited by 39
“proposed [21]–[23] to reduce beam hardening artifacts.”
Dang, H., Stayman, J. W., Sisniega, A., et al. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/16/6153 · Cited by 38
“(16) in (Joseph and Spital 1978) (polynomials not written out for simplicity): (12c) where lbone denotes the line integrals of the bony structures, and λ0 represents the ratio of the bone mass attenuation coefficient to the water mass attenuation coefficient.”
BackgroundMethodInfluentialBeam Hardening Correction for Middle-Energy Industrial Computerized Tomography
Gao, H., Zhang, L., Chen, Z., et al. (2006) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2006.879825 · Cited by 38
“In [6] and [9], postprocessing methods are introduced to correct the beam hardening in objects containing soft tissues and bones.”
BackgroundMethodInfluentialModulator design for x‐ray scatter correction using primary modulation: Material selection
Gao, H., Zhu, L., & Fahrig, R. (2010) · Medical Physics · doi:10.1118/1.3457472 · Cited by 36
Alberico, R. A., Loud, P. A., Pollina, J., et al. (2000) · American Journal of Roentgenology · doi:10.2214/ajr.175.5.1751361 · Cited by 36
Machida, H., TAKEUCHI, H., Tanaka, I., et al. (2013) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3320 · Cited by 35
“Previous studies have used a variety of technologies to decrease these artifacts, including the use of newer multidetector CT machines using a helical scan technique with thinner image collimation, higher output tubes, and better reconstruction algorithms (such as beam-hardening correction and iterative reconstruction…”
MethodAy, M. R., Mehranian, A., Maleki, A., et al. (2012) · Physica Medica · doi:10.1016/j.ejmp.2012.03.005 · Cited by 35
“In post-processing, the problem of bones is fairly tackled, since the contribution made by bone to projection data is determined in a reconstructionsegmentation process and appropriate correction is applied through linearization [18].”
MethodBeam Hardening Correction Using Cone Beam Consistency Conditions
Abdurahman, S., Frysch, R., Bismark, R., Melnik, S., Beuing, O., & Rose, G. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2840343 · Cited by 36
“Joseph and Spital [5] proposed a method to correct bone induced artifacts for fan beam CT using the forward projection of segmented bone volumes.”
BackgroundMethodInfluentialApplications of Computed Tomography in Radiotherapy Treatment Planning
Goitein, M. (1982) · Springer eBooks · doi:10.1007/978-1-4615-7691-4_4 · Cited by 35
C-arm orbits for metal artifact avoidance (MAA) in cone-beam CT
Wu, P., Sheth, N., Sisniega, A., et al. (2020) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ab9454 · Cited by 34
“…raising the pixel value pmono (u, v|θ, ϕ) to the power of i, αi are precalculated polynomial mapping coefficients, which are determined not only by the spectrum but also the metal material (since the energy dependence of attenuation coefficient is material dependent) (Joseph and Spital 1978).”
BackgroundInfluentialStreak Preventive Image Reconstruction with ART and Adaptive Filtering
Rangayyan, R. M., & Gordon, R. (1982) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1982.4307569 · Cited by 34
Wu, P., Sisniega, A., Stayman, J. W., et al. (2020) · Medical Physics · doi:10.1002/mp.14124 · Cited by 32
Past and future directions in x‐ray computed tomography (CT)
Natterer, F., & Ritman, E. L. (2002) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.10021 · Cited by 32
“Hence, software methods for mitigating the beam hardening are also a routine package in most scanners (Joseph and Spital, 1978).”
MethodKubo, M., Niki, N., Nakagawa, S., et al. (1999) · IEEE Transactions on Nuclear Science · doi:10.1109/23.819294 · Cited by 32
Characterization of Metal Artifacts in X-ray Computed TomographyPreprint
Suk, H., Jae, P., Jin, K. C., & Seo, K. (2016) · Cited by 28
Lin, Y., & Samei, E. (2014) · Medical Physics · doi:10.1118/1.4863481 · Cited by 31
Tilley, S., Zbijewski, W. B., & Stayman, J. W. (2018) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aaf973 · Cited by 31
“Additionally, IDD may require separate correction for spectral effects such as beamhardening (Joseph and Spital 1978).”
BackgroundCharting the course towards dimensional measurement traceability by x-ray computed tomography
Ferrucci, M., & Ametova, E. (2021) · Measurement Science and Technology · doi:10.1088/1361-6501/abf058 · Cited by 30
Exact treatment of the dual-energy method in CT using polyenergetic x-ray spectra
Christ, G. (1984) · Physics in Medicine and Biology · doi:10.1088/0031-9155/29/12/005 · Cited by 30
Computed tomography in planning radiation therapy
Goitein, M. (1979) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/0360-3016(79)91230-6 · Cited by 30
Hampel, U. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-823015-2.00029-7 · Cited by 29
A digitally reconstructed radiograph algorithm calculated from first principles
Staub, D., & Murphy, M. J. (2012) · Medical Physics · doi:10.1118/1.4769413 · Cited by 30
Quantitative image‐based spectral reconstruction for computed tomography
Heismann, B. J., & Balda, M. (2009) · Medical Physics · doi:10.1118/1.3213534 · Cited by 29
Removal of bone in CT angiography by multiscale matched mask bone elimination
van Andel, H. A. F. G., Venema, H. W., Streekstra, G. J., et al. (2007) · Medical Physics · doi:10.1118/1.2767931 · Cited by 28
CT artifact correction: an image-processing approach
Soltanian‐Zadeh, H., Windham, J. P., & Soltanianzadeh, J. (1996) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.237950 · Cited by 28
“There are several physics based methods for correcting streaking artifacts [6], [7], [8].”
MethodSemerci, O., & Miller, E. L. (2012) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2186308 · Cited by 27
Robust Beam Hardening Artifacts Reduction for Computed Tomography Using Spectrum Modeling
Zhao, W. P., Li, D., Niu, K., et al. (2018) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2018.2884479 · Cited by 27
“induced artifacts correction [35], [36].”
Semerci, O., Miller, E. L., & Member, S. (2012) · Cited by 26
Simplified Statistical Image Reconstruction for X-ray CT With Beam-Hardening Artifact Compensation
Abella, M., Martínez, C., Desco, M., et al. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2921929 · Cited by 25
“To overcome this problem, we modify the projection model by adapting one idea previously proposed by Joseph and Spital [8].”
BackgroundMethodInfluentialNicholson, P. J., Cancelliere, N. M., Bracken, J. A., et al. (2021) · European Journal of Radiology · doi:10.1016/j.ejrad.2021.109645 · Cited by 25
Metadata
- Authors
- Joseph, P. M., & Spital, R. D.
- Affiliations
- NewYork–Presbyterian Hospital (US)
- Venue
- Journal of Computer Assisted Tomography
- Published
- 1978-01
- Volume
- 2
- Issue
- 1
- Pages
- 100-108
- ISSN
- 0363-8715 (ISSN-L)
- OpenAlex
- W2000441297
- Cited by
- 281
- References
- 0
- Citations by year
- 2026: 7 · 2025: 4 · 2024: 10 · 2023: 6 · 2022: 13 · 2021: 6 · 2020: 9 · 2019: 12 · 2018: 17 · 2017: 10 · 2016: 10 · 2015: 9 · 2014: 10 · 2013: 10 · 2012: 13
- FWCI
- 8.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computer Assisted Tomography (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced X-ray and CT Imaging
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiation Dose and Imaging
- Keywords
- bone artifacts, spectral artifacts, X-ray spectra, streak artifacts, head CT, image reconstruction, mathematical phantoms
- MeSH terms
- Bone and Bones, Humans, Mathematics, Models, Structural, Skull, Technology, Radiologic, Tomography, X-Ray Computed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review