21.8.5 Tomographic Images, Artifact Removal, Artefacts, Enhancement

Chapter Contents (Back)
Enhancement. Artifact Removal. Artefact Removal. Noise. Tomography.

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The tuning fork artifact in computerized tomography,
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Pan, X., Yu, L., Kao, C.M.,
Spatial-Resolution Enhancement in Computed Tomography,
MedImg(24), No. 2, February 2005, pp. 246-253.
IEEE Abstract. 0501
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La Riviere, P.J., Billmire, D.M.,
Reduction of noise-induced streak artifacts in X-ray computed tomography through spline-based penalized-likelihood sinogram smoothing,
MedImg(24), No. 1, January 2005, pp. 105-111.
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La Riviere, P.J., Bian, J., Vargas, P.A.,
Penalized-Likelihood Sinogram Restoration for Computed Tomography,
MedImg(25), No. 8, August 2006, pp. 1022-1036.
IEEE DOI 0608
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Wang, J., Li, T., Lu, H., Liang, Z.,
Penalized Weighted Least-Squares Approach to Sinogram Noise Reduction and Image Reconstruction for Low-Dose X-Ray Computed Tomography,
MedImg(25), No. 10, October 2006, pp. 1272-1283.
IEEE DOI 0609
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Zhu, L., Bennett, N.R., Fahrig, R.,
Scatter Correction Method for X-Ray CT Using Primary Modulation: Theory and Preliminary Results,
MedImg(25), No. 12, December 2006, pp. 1573-1587.
IEEE DOI 0701
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Desbat, L., Roux, S., Grangeat, P.,
Compensation of Some Time Dependent Deformations in Tomography,
MedImg(26), No. 2, February 2007, pp. 261-269.
IEEE DOI 0702
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Gravier, E.[Erwan], Yang, Y.Y.[Yong-Yi], Jin, M.[Mingwu],
Tomographic Reconstruction of Dynamic Cardiac Image Sequences,
IP(16), No. 4, April 2007, pp. 932-942.
IEEE DOI 0704
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Earlier: A1, A2, Only:
Motion-compensated reconstruction of tomographic image sequences,
ICIP03(II: 807-810).
IEEE DOI 0312
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Salinas, H.M., Fernandez, D.C.,
Comparison of PDE-Based Nonlinear Diffusion Approaches for Image Enhancement and Denoising in Optical Coherence Tomography,
MedImg(26), No. 6, June 2007, pp. 761-771.
IEEE DOI 0706
BibRef

Arivazhagan, S., Deivalakshmi, S., Kannan, K., Gajbhiye, B.N., Muralidhar, C., Lukose, S.N.[Sijo N.], Subramanian, M.P.,
Multi-resolution system for artifact removal and edge enhancement in computerized tomography images,
PRL(28), No. 13, 1 October 2007, pp. 1769-1780.
Elsevier DOI 0709
Industrial CT images; Edge enhancement; Multi-resolution techniques BibRef

Schaap, M., Schilham, A.M.R., Zuiderveld, K.J., Prokop, M., Vonken, E.J., Niessen, W.J.,
Fast Noise Reduction in Computed Tomography for Improved 3-D Visualization,
MedImg(27), No. 8, August 2008, pp. 1120-1129.
IEEE DOI 0808
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Liu, Y.H.[Yi-Heng], Liang, Y.M.[Yan-Mei], Mu, G.G.[Guo-Guang], Zhu, X.N.[Xiao-Nong],
Deconvolution methods for image deblurring in optical coherence tomography,
JOSA-A(26), No. 1, January 2009, pp. 72-77.
WWW Link. 0804
BibRef

Lemmens, C., Faul, D., Nuyts, J.,
Suppression of Metal Artifacts in CT Using a Reconstruction Procedure That Combines MAP and Projection Completion,
MedImg(28), No. 2, February 2009, pp. 250-260.
IEEE DOI 0902
BibRef

Mendrik, A.M.[Adriënne M.], Vonken, E.J., Rutten, A., Viergever, M.A., van Ginneken, B.,
Noise Reduction in Computed Tomography Scans Using 3-D Anisotropic Hybrid Diffusion With Continuous Switch,
MedImg(28), No. 10, October 2009, pp. 1585-1594.
IEEE DOI 0910
BibRef

Segars, W.P., Tsui, B.M.W.,
MCAT to XCAT: The Evolution of 4-D Computerized Phantoms for Imaging Research,
PIEEE(97), No. 12, December 2009, pp. 1954-1968.
IEEE DOI 0912
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Johnson, P.B., Whalen, S.R., Wayson, M., Juneja, B., Lee, C., Bolch, W.E.,
Hybrid Patient-Dependent Phantoms Covering Statistical Distributions of Body Morphometry in the U.S. Adult and Pediatric Population,
PIEEE(97), No. 12, December 2009, pp. 2060-2075.
IEEE DOI 0912
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Zhang, G., Xie, T., Bosmans, H., Liu, Q.,
Development of a Rat Computational Phantom Using Boundary Representation Method for Monte Carlo Simulation in Radiological Imaging,
PIEEE(97), No. 12, December 2009, pp. 2006-2014.
IEEE DOI 0912
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Stobbe, R.W., Beaulieu, C.,
Assessment of Averaging Spatially Correlated Noise for 3-D Radial Imaging,
MedImg(30), No. 7, July 2011, pp. 1381-1390.
IEEE DOI 1107
BibRef

Hasan, M.K.[Md. Kamrul], Sadi, F.[Fazle], Lee, S.Y.[Soo Yeol],
Removal of ring artifacts in micro-CT imaging using iterative morphological filters,
SIViP(6), No. 1, March 2012, pp. 41-53.
WWW Link. 1203
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Wang, J.[Jia], Song, Y.[Yang], Li, Z.H.[Zhen-Hua], Sun, N.[Nan], He, A.Z.[An-Zhi],
Theoretical analysis for moiré effect of circular gratings for volume optical computerized tomography,
JOSA-A(29), No. 8, August 2012, pp. 1686-1693.
WWW Link. 1208
BibRef

Zhang, Y.[Yi], Pu, Y.F.[Yi-Fei], Zhang, W.H.[Wei-Hua], Hu, J.R.[Jin-Rong], Wang, H.[Han], Lei, Y.J.[Yin-Jie], Zhou, J.L.[Ji-Liu],
A novel noniterative metal artifact reduction method using coherence transport with fast marching in computed tomography,
IJIST(22), No. 4, December 2012, pp. 200-207.
DOI Link 1211
BibRef

Lin, C.H.[Chuen-Horng], Lin, C.Y.[Chih-Yang], Cheng, Y.J.[Yu-Jung], Chan, Y.K.[Yung-Kuan],
An automatic evaluation system for contrast-detail phantom images in digital radiography,
IJIST(22), No. 4, December 2012, pp. 214-225.
DOI Link 1211
BibRef

Rodrigues, P., Bernardes, R.,
3-D Adaptive Nonlinear Complex-Diffusion Despeckling Filter,
MedImg(31), No. 12, December 2012, pp. 2205-2212.
IEEE DOI 1212
BibRef

Mehranian, A., Ay, M.R., Rahmim, A., Zaidi, H.,
X-ray CT Metal Artifact Reduction Using Wavelet Domain L_0 Sparse Regularization,
MedImg(32), No. 9, 2013, pp. 1707-1722.
IEEE DOI 1309
L_0 sparse regularization BibRef

Paiement, A.[Adeline],
Extended Abstract of PhD Thesis: Integrated Registration, Segmentation, and Interpolation for 3D/4D Sparse Data,
ELCVIA(14), No. 3, 2015, pp. xx-yy.
DOI Link 1601
BibRef

Paiement, A., Mirmehdi, M., Xie, X.H.[Xiang-Hua], Hamilton, M.C.K.,
Integrated Segmentation and Interpolation of Sparse Data,
IP(23), No. 1, January 2014, pp. 110-125.
IEEE DOI 1402
image reconstruction BibRef

Plautz, T., Bashkirov, V., Feng, V., Hurley, F., Johnson, R.P., Leary, C., Macafee, S., Plumb, A., Rykalin, V., Sadrozinski, H.F.W., Schubert, K., Schulte, R., Schultze, B., Steinberg, D., Witt, M., Zatserklyaniy, A.,
200 MeV Proton Radiography Studies With a Hand Phantom Using a Prototype Proton CT Scanner,
MedImg(33), No. 4, April 2014, pp. 875-881.
IEEE DOI 1404
Computed tomography BibRef

Al-Ameen, Z.[Zohair], Sulong, G.[Ghazali],
Attenuating noise from computed tomography medical images using a coefficients-driven total variation denoising algorithm,
IJIST(24), No. 4, 2014, pp. 350-358.
DOI Link 1411
coefficients-driven total variation BibRef

Al-Ameen, Z.[Zohair], Sulong, G.[Ghazali],
A novel Zohair filter for deblurring computed tomography medical images,
IJIST(25), No. 3, 2015, pp. 265-275.
DOI Link 1509
computed tomography, image deblurring, Zohair filter BibRef

Chen, Y.[Yang], Shi, L.[Luyao], Feng, Q.J.[Qian-Jing], Yang, J.[Jian], Shu, H.Z.[Hua-Zhong], Luo, L.M.[Li-Min], Coatrieux, J.L., Chen, W.F.[Wu-Fan],
Artifact Suppressed Dictionary Learning for Low-Dose CT Image Processing,
MedImg(33), No. 12, December 2014, pp. 2271-2292.
IEEE DOI 1412
biological organs BibRef

Yan, Z.Y.[Zi-Ye], Li, J.W.[Jian-Wu], Lu, Y.[Yao], Yan, H.X.[Hong-Xia], Zhao, Y.F.[Yan-Feng],
Super resolution in CT,
IJIST(25), No. 1, 2015, pp. 92-101.
DOI Link 1502
computed tomography BibRef

Petrongolo, M., Zhu, L.[Lei],
Noise Suppression for Dual-Energy CT Through Entropy Minimization,
MedImg(34), No. 11, November 2015, pp. 2286-2297.
IEEE DOI 1512
BibRef
And: Erratum: MedImg(34), No. 12, December 2015, pp. 2646-2646.
IEEE DOI 1601
Computed tomography BibRef

Park, H.S., Hwang, D., Seo, J.K.,
Metal Artifact Reduction for Polychromatic X-ray CT Based on a Beam-Hardening Corrector,
MedImg(35), No. 2, February 2016, pp. 480-487.
IEEE DOI 1602
Approximation methods BibRef

Titarenko, V.,
1-D Filter for Ring Artifact Suppression,
SPLetters(23), No. 6, June 2016, pp. 800-804.
IEEE DOI 1606
computerised tomography BibRef

Diwakar, M.[Manoj], Kumar, M.[Manoj],
CT image denoising using NLM and correlation-based wavelet packet thresholding,
IET-IPR(12), No. 5, May 2018, pp. 708-715.
DOI Link 1804
BibRef

Tao, H.J.[Huan-Jie], Lu, X.B.[Xiao-Bo],
Correction of micro-CT image geometric artefacts based on marker,
IET-IPR(12), No. 6, June 2018, pp. 888-895.
DOI Link 1805
BibRef

Zhang, Y., Yu, H.,
Convolutional Neural Network Based Metal Artifact Reduction in X-Ray Computed Tomography,
MedImg(37), No. 6, June 2018, pp. 1370-1381.
IEEE DOI 1806
Attenuation, Bones, Computed tomography, Convolutional neural networks, Databases, Image reconstruction, metal artifacts BibRef

Chang, Z., Ye, D.H., Srivastava, S., Thibault, J., Sauer, K., Bouman, C.,
Prior-Guided Metal Artifact Reduction for Iterative X-Ray Computed Tomography,
MedImg(38), No. 6, June 2019, pp. 1532-1542.
IEEE DOI 1906
Metals, Image reconstruction, Photonics, X-ray imaging, Computed tomography, Solid modeling, Adaptation models, computed tomography BibRef

Liao, H., Lin, W., Zhou, S.K., Luo, J.,
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction,
MedImg(39), No. 3, March 2020, pp. 634-643.
IEEE DOI 2004
Metals, Computed tomography, Decoding, Mars, X-ray imaging, Image reconstruction, Training, computed tomography BibRef

Pivot, O., Fournier, C., Tabary, J., Letang, J.M., Rit, S.,
Scatter Correction for Spectral CT Using a Primary Modulator Mask,
MedImg(39), No. 6, June 2020, pp. 2267-2276.
IEEE DOI 2006
Photon counting detectors, primary modulator mask, scatter correction, spectral CT BibRef

Xu, J., Noo, F.,
A Robust Regularizer for Multiphase CT,
MedImg(39), No. 7, July 2020, pp. 2327-2338.
IEEE DOI 2007
TV, Computed tomography, Convolution, Image denoising, Image reconstruction, Image quality, Huber function, total variation BibRef

Preuhs, A., Manhart, M., Roser, P., Hoppe, E., Huang, Y., Psychogios, M., Kowarschik, M., Maier, A.,
Appearance Learning for Image-Based Motion Estimation in Tomography,
MedImg(39), No. 11, November 2020, pp. 3667-3678.
IEEE DOI 2011
Image reconstruction, Magnetic resonance imaging, Geometry, Tomography, Motion compensation, Trajectory, appearance learning BibRef

Li, Z.[Zhi], Jia, Z.H.[Zhen-Hong], Yang, J.[Jie], Kasabov, N.[Nikola],
An efficient and high quality medical CT image enhancement algorithm,
IJIST(30), No. 4, 2020, pp. 939-949.
DOI Link 2011
histogram equalization, medical image, wavelet transform BibRef

Peng, C., Li, B., Liang, P., Zheng, J., Zhang, Y., Qiu, B., Chen, D.Z.,
A Cross-Domain Metal Trace Restoring Network for Reducing X-Ray CT Metal Artifacts,
MedImg(39), No. 12, December 2020, pp. 3831-3842.
IEEE DOI 2012
Metals, Image restoration, Computed tomography, Implants, X-ray imaging, Image reconstruction, Decoding, Cross-domain, fan-beam CT BibRef

Yu, L., Zhang, Z., Li, X., Xing, L.,
Deep Sinogram Completion With Image Prior for Metal Artifact Reduction in CT Images,
MedImg(40), No. 1, January 2021, pp. 228-238.
IEEE DOI 2012
Metals, Computed tomography, Image reconstruction, Neural networks, Image generation, Interpolation, Image restoration, deep learning BibRef

Huang, Y.X.[Yi-Xing], Preuhs, A.[Alexander], Manhart, M.[Michael], Lauritsch, G.[Guenter], Maier, A.[Andreas],
Data Extrapolation From Learned Prior Images for Truncation Correction in Computed Tomography,
MedImg(40), No. 11, November 2021, pp. 3042-3053.
IEEE DOI 2111
Image reconstruction, Deep learning, Computed tomography, Extrapolation, Detectors, Image quality, Robustness, Deep learning, computed tomography BibRef

Bai, T.[Ti], Wang, B.[Biling], Nguyen, D.[Dan], Wang, B.[Bao], Dong, B.[Bin], Cong, W.X.[Wen-Xiang], Kalra, M.K.[Mannudeep K.], Jiang, S.[Steve],
Deep Interactive Denoiser (DID) for X-Ray Computed Tomography,
MedImg(40), No. 11, November 2021, pp. 2965-2975.
IEEE DOI 2111
Computed tomography, Image resolution, Training, Noise reduction, Task analysis, X-ray imaging, Testing, Deep learning, image denoising BibRef

Lee, J.[Junghyun], Gu, J.[Jawook], Ye, J.C.[Jong Chul],
Unsupervised CT Metal Artifact Learning Using Attention-Guided ß-CycleGAN,
MedImg(40), No. 12, December 2021, pp. 3932-3944.
IEEE DOI 2112
Metals, Computed tomography, Mars, Image reconstruction, Deep learning, Dentistry, Unsupervised learning, convolutional block attention module BibRef

Zavala-Mondragón, L.A.[Luis Albert], de With, P.H.N.[Peter H. N.], van der Sommen, F.[Fons],
Image Noise Reduction Based on a Fixed Wavelet Frame and CNNs Applied to CT,
IP(30), 2021, pp. 9386-9401.
IEEE DOI 2112
Noise reduction, Discrete wavelet transforms, Wireless sensor networks, Computed tomography, Kernel, Convolution, denoising BibRef

Geng, M.F.[Mu-Feng], Meng, X.X.[Xiang-Xi], Yu, J.Y.[Jiang-Yuan], Zhu, L.[Lei], Jin, L.[Lujia], Jiang, Z.[Zhe], Qiu, B.[Bin], Li, H.[Hui], Kong, H.[Hanjing], Yuan, J.M.[Jian-Min], Yang, K.[Kun], Shan, H.M.[Hong-Ming], Han, H.B.[Hong-Bin], Yang, Z.[Zhi], Ren, Q.S.[Qiu-Shi], Lu, Y.Y.[Yan-Ye],
Content-Noise Complementary Learning for Medical Image Denoising,
MedImg(41), No. 2, February 2022, pp. 407-419.
IEEE DOI 2202
Biomedical imaging, Noise reduction, Image denoising, Computed tomography, Generative adversarial networks, image restoration BibRef

Wang, H.[Hong], Li, Y.X.[Yue-Xiang], He, N.J.[Nan-Jun], Ma, K.[Kai], Meng, D.Y.[De-Yu], Zheng, Y.F.[Ye-Feng],
DICDNet: Deep Interpretable Convolutional Dictionary Network for Metal Artifact Reduction in CT Images,
MedImg(41), No. 4, April 2022, pp. 869-880.
IEEE DOI 2204
Computed tomography, Metals, Task analysis, Dictionaries, Mars, Optimization, Image reconstruction, CT metal artifact reduction, interpretable dictionary learning BibRef

Juneja, M.[Mamta], Joshi, S.[Saasha], Singla, N.[Naveen], Ahuja, S.[Shaurya], Saini, S.K.[Sumindar Kaur], Thakur, N.[Niharika], Jindal, P.[Prashant],
Denoising of computed tomography using bilateral median based autoencoder network,
IJIST(32), No. 3, 2022, pp. 935-955.
DOI Link 2205
autoencoders, bilateral median, CT scan, denoising, filtering, pancreatic cancer BibRef

Zavala-Mondragon, L.A.[Luis A.], Rongen, P.[Peter], Bescos, J.O.[Javier Olivan], de With, P.H.N.[Peter H. N.], van der Sommen, F.[Fons],
Noise Reduction in CT Using Learned Wavelet-Frame Shrinkage Networks,
MedImg(41), No. 8, August 2022, pp. 2048-2066.
IEEE DOI 2208
Noise reduction, Discrete wavelet transforms, Convolutional neural networks, Convolution, Computed tomography, encoding-decoding BibRef

Rao, K.[Karishma], Bansal, M.[Manu], Kaur, G.[Gagandeep],
An optimized morphology transform-based diagnostic computed tomography image enhancement using edge map,
IJIST(32), No. 5, 2022, pp. 1743-1760.
DOI Link 2209
CT image, image enhancement, PSO, top hat transform BibRef

Gan, W.J.[Wei-Jie], Sun, Y.[Yu], Eldeniz, C.[Cihat], Liu, J.M.[Jia-Ming], An, H.Y.[Hong-Yu], Kamilov, U.S.[Ulugbek S.],
Deformation-Compensated Learning for Image Reconstruction Without Ground Truth,
MedImg(41), No. 9, September 2022, pp. 2371-2384.
IEEE DOI 2209
Training, Magnetic resonance imaging, Noise measurement, Image reconstruction, Strain, Imaging, magnetic resonance imaging (MRI) BibRef

Xie, M.Y.[Ming-Yang], Liu, J.M.[Jia-Ming], Sun, Y.[Yu], Gan, W.J.[Wei-Jie], Wohlberg, B.[Brendt], Kamilov, U.S.[Ulugbek S.],
Joint Reconstruction and Calibration Using Regularization by Denoising with Application to Computed Tomography,
LCI21(4011-4020)
IEEE DOI 2112
Uncertainty, Limiting, Computed tomography, Noise reduction, Measurement uncertainty, Robustness, Calibration BibRef

Du, M.[Muge], Liang, K.[Kaichao], Zhang, L.[Li], Gao, H.[Hewei], Liu, Y.[Yinong], Xing, Y.X.[Yu-Xiang],
Deep-Learning-Based Metal Artefact Reduction With Unsupervised Domain Adaptation Regularization for Practical CT Images,
MedImg(42), No. 8, August 2023, pp. 2133-2145.
IEEE DOI 2308
Mars, Metals, Computed tomography, Feature extraction, Training, Task analysis, Measurement, X-ray imaging and computed tomography BibRef

Wang, H.[Hong], Xie, Q.[Qi], Zeng, D.[Dong], Ma, J.H.[Jian-Hua], Meng, D.Y.[De-Yu], Zheng, Y.F.[Ye-Feng],
OSCNet: Orientation-Shared Convolutional Network for CT Metal Artifact Learning,
MedImg(43), No. 1, January 2024, pp. 489-502.
IEEE DOI Code:
WWW Link. 2401
BibRef


Bera, S.[Sutanu], Biswas, P.K.[Prabir Kumar],
Gated Convolutional Network for Metal Artifact Reduction in Computed Tomography Images,
ICIP22(4118-4122)
IEEE DOI 2211
Visualization, Art, Convolution, Computed tomography, Metals, Logic gates, Image restoration, Gated Convolution Network BibRef

Seo, M.[Minkyo], Kim, D.[Dongkeun], Lee, K.[Kyungmoon], Hong, S.[Seunghoon], Bae, J.S.[Jae Seok], Kim, J.H.[Jung Hoon], Kwak, S.[Suha],
Neural Contrast Enhancement of CT Image,
WACV21(3972-3981)
IEEE DOI 2106
Training, Deep learning, Image synthesis, Computed tomography, Neural networks, Predictive models, Registers BibRef

Lin, W.A.[Wei-An], Liao, H.[Haofu], Peng, C.[Cheng], Sun, X.H.[Xiao-Hang], Zhang, J.D.[Jing-Dan], Luo, J.B.[Jie-Bo], Chellappa, R.[Rama], Zhou, S.H.K.[Shao-Hua Kevin],
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction,
CVPR19(10504-10513).
IEEE DOI 2002
BibRef

Jin, K.C.[Kyung-Chan], Yoon, J.S.[Jung-Seok], Song, Y.H.[Yoon-Ho],
Reduction of Missing Wedge Artifact in Oblique-View Computed Tomography,
ISVC16(II: 475-482).
Springer DOI 1701
BibRef

Frédérique, L.[Louis], Recur, B.[Benoit], Genot, S.[Sylvain], Domenger, J.P.[Jean-Philippe], Desbarats, P.[Pascal],
Sinogram Restoration Using Confidence Maps to Reduce Metal Artifact in Computed Tomography,
ICIAR16(81-89).
Springer DOI 1608
BibRef

Sreehari, S.[Suhas], Venkatakrishnan, S.V., Drummy, L.[Lawrence], Simmons, J.[Jeff], Bouman, C.A.[Charles A.],
Rotationally-invariant non-local means for image denoising and tomography,
ICIP15(542-546)
IEEE DOI 1512
Rotationally-invariant NLM BibRef

Jin, P.C.[Peng-Chong], Ye, D.H.[Dong Hye], Bouman, C.A.[Charles A.],
Joint metal artifact reduction and segmentation of CT images using dictionary-based image prior and continuous-relaxed potts model,
ICIP15(798-802)
IEEE DOI 1512
Dictionary Learning BibRef

Kumar, A.[Arjun], Mandal, P.[Pratiti], Zhang, Y.J.J.[Yong-Jie Jessica], Litster, S.[Shawn],
Image Restoration of Phase Contrast Nano Scale X-ray CT Images,
CompIMAGE14(280-285).
Springer DOI 1407
BibRef

Kiwanuka, F.N.[Fred N.], Wilkinson, M.H.F.[Michael H. F.],
Cluster Based Vector Attribute Filtering,
ISMM15(277-288).
Springer DOI 1506
BibRef
Earlier:
Cluster-based vector-attribute filtering for CT and MRI enhancement,
ICPR12(3112-3115).
WWW Link. 1302
BibRef

Karimi, S.[Seemeen], Cosman, P.[Pamela], Wald, C.[Christoph], Martz, H.[Harry],
Using segmentation in CT metal artifact reduction,
Southwest12(9-12).
IEEE DOI 1205
BibRef

Brun, F., Kourousias, G., Dreossi, D., Mancini, L., Tromba, G.,
A comparative evaluation of ring artifacts reduction filters for X-ray computed microtomography images,
ICIP11(405-408).
IEEE DOI 1201
BibRef

Kim, D.S.[Dong Sik], Lee, S.G.[Sang-Gyun],
Adaptive grid pattern artifact reduction in radiography imaging based on the significant-signal bandwidth,
ICIP11(1473-1476).
IEEE DOI 1201
BibRef
Earlier:
Grid artifact reduction in radiography with arctan(1/2)-degree rotated grid,
ICIP10(1957-1960).
IEEE DOI 1009
BibRef

Kim, Y.S.[Young-Shin], Yoon, S.B.[Seong-Beak], Yi, J.H.[June-Ho],
Effective sinogram-inpainting for metal artifacts reduction in X-ray CT images,
ICIP10(597-600).
IEEE DOI 1009
BibRef

Pan, N.[Ning], Liu, H.[Hong], de Ruiter, N., Grasset, R.,
Improving the image quality of spectral CT volume rendering,
IVCNZ09(203-208).
IEEE DOI 0911
BibRef

Huang, K.D.[Kui-Dong], Zhang, D.H.[Ding-Hua], Li, M.J.[Ming-Jun],
Noise Suppression Methods in Beam Hardening Correction for X-Ray Computed Tomography,
CISP09(1-5).
IEEE DOI 0910
BibRef

Chandra, S.[Shekhar], Svalbe, I.[Imants],
A method for removing cyclic artefacts in discrete tomography using latin squares,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Axelsson, M.[Maria], Svensson, S.[Stina], Borgefors, G.[Gunilla],
Reduction of Ring Artifacts in High Resolution X-Ray Microtomography Images,
DAGM06(61-70).
Springer DOI 0610
BibRef

Yuasa, T., Devaraj, B., Tanosaki, S., Taniguchi, H., Akatsuka, T.,
Reconstruction Method for Compensation of Surface Effects in Transillumination Laser CT,
ICIP01(I: 341-344).
IEEE DOI 0108
BibRef

Hassanien, A.E., Karam, H., Akter, H., Nakajima, M.,
Generation of Missing Medical Slices Using Morphing Technology,
MVA98(xx-yy). BibRef 9800

Garren, D.A., Goldstein, J.S.,
Extraction of multiple-bounce artifacts in tomographic imaging,
ICIP02(II: 613-616).
IEEE DOI 0210
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Electrical Impedance Tomography, EIT .


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