21.8.4 Tomographic Image Generation, CAT, CT, Reconstruction

Chapter Contents (Back)
Reconstruction. CT. CAT. Tomography.
See also Tomographic Image Reconstruction, Random Projections, Unknown Projections.
See also Statistical, Bayesian Tomographic Image Reconstruction.
See also Few Views, Limited Views, Low Dose, Tomographic Image Reconstruction.
See also Fluorescence Tomography, X-ray Fluorescence Computed Tomography XFCT.
See also Backprojection in Tomographic Image Reconstruction. Space issues:
See also Ionosphere, Ionosphere Tomography, Reflections, Ionospheric Effects, TEC.

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Earlier:
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Fessler, J.A.,
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And: Correction: IP(5), No. 9, September 1996, pp. 1390.
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Fessler, J.A.,
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Yu, D.F., Fessler, J.A.,
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Fessler, J.A., Sutton, B.P.,
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Akiyama, I.,
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Matej, S., Herman, G.T., Vardi, A.,
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Bonnet, S., Peyrin, F., Turjman, F., Prost, R.,
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Lai, J.Y.[Jiing-Yih], Doong, J.L.[Ji-Liang], Yao, C.Y.[Chia-Yu],
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Yan, C.H.[Chye Hwang], Whalen, R.T., Beaupre, G.S., Yen, S.Y., Napel, S.,
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Miyakawa, M., Orikasa, K., Bertero, M., Boccacci, P., Conte, F., Piana, M.,
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Kalifa, J., Laine, A., Esser, P.D.,
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Qureshi, S.A., Mirza, S.M., Rajpoot, N.M., Arif, M.,
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Ăoelker Karbeyaz, B., Naidu, R.C., Ying, Z., Simanovsky, S.B., Hirsch, M.W., Schafer, D.A., Crawford, C.R.,
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Karbeyaz, E.[Ersel], Rappaport, C.M.[Carey M.],
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Zonoobi, D.[Dornoosh], Kassim, A.A.[Ashraf A.],
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Compressive sensing; Compressive sampling; Weighted l_1 minimization; Probability model; Sequential CS; Priori knowledge; Time-varying signals; Medical image reconstruction BibRef

Venkatesh, Y.V., Kassim, A.A.[Ashraf A.], Zonoobi, D.[Dornoosh],
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Eyraud, C.[Christelle], Vaillon, R.[Rodolphe], Litman, A.[Amélie], Geffrin, J.M.[Jean-Michel], Merchiers, O.[Olivier],
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IEEE DOI 1404
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IEEE DOI 1408
Computed tomography BibRef

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IEEE DOI 1502
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computerised tomography BibRef

Kim, D.H.[Dong-Hwan], Ramani, S., Fessler, J.A.,
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IEEE DOI 1502
computerised tomography BibRef

Ward, J.P.[John Paul], Lee, M.J.[Min-Ji], Ye, J.C.[Jong Chul], Unser, M.[Michael],
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Lee, M.J.[Min-Ji], Han, Y.[Yoseob], Ward, J.P.[John Paul], Unser, M.[Michael], Ye, J.C.[Jong Chul],
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Dubey, S.R., Singh, S.K., Singh, R.K.,
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SPLetters(22), No. 9, September 2015, pp. 1215-1219.
IEEE DOI 1503
computerised tomography BibRef

Dubey, S.R., Singh, S.K., Singh, R.K.,
Local neighbourhood-based robust colour occurrence descriptor for colour image retrieval,
IET-IPR(9), No. 7, 2015, pp. 578-586.
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content-based retrieval BibRef

Dubey, S.R., Singh, S.K., Singh, R.K.,
Local Wavelet Pattern: A New Feature Descriptor for Image Retrieval in Medical CT Databases,
IP(24), No. 12, December 2015, pp. 5892-5903.
IEEE DOI 1512
computerised tomography BibRef

Dubey, S.R., Singh, S.K., Singh, R.K.,
Multichannel Decoded Local Binary Patterns for Content-Based Image Retrieval,
IP(25), No. 9, September 2016, pp. 4018-4032.
IEEE DOI 1609
channel coding BibRef

Zhao, Y.S.[Yun-Song], Zhao, X.[Xing], Zhang, P.[Peng],
An Extended Algebraic Reconstruction Technique (E-ART) for Dual Spectral CT,
MedImg(34), No. 3, March 2015, pp. 761-768.
IEEE DOI 1503
X-ray spectra BibRef

Rakvongthai, Y., Worstell, W., El Fakhri, G., Bian, J.G.[Jun-Guo], Lorsakul, A., Ouyang, J.S.[Jin-Song],
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MedImg(34), No. 3, March 2015, pp. 740-747.
IEEE DOI 1503
X-ray tubes BibRef

Li, L.[Liang], Chen, Z.Q.[Zhi-Qiang], Cong, W.X.[Wen-Xiang], Wang, G.[Ge],
Spectral CT Modeling and Reconstruction With Hybrid Detectors in Dynamic-Threshold-Based Counting and Integrating Modes,
MedImg(34), No. 3, March 2015, pp. 716-728.
IEEE DOI 1503
compressed sensing BibRef

Kim, K.[Kyungsang], Ye, J.C.[Jong Chul], Worstell, W., Ouyang, J.S.[Jin-Song], Rakvongthai, Y., El Fakhri, G., Li, Q.Z.[Quan-Zheng],
Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty,
MedImg(34), No. 3, March 2015, pp. 748-760.
IEEE DOI 1503
Poisson distribution BibRef

Papadaniil, C.D.[Chrysa D.], Hadjileontiadis, L.J.[Leontios J.],
Tomographic Reconstruction of 3-D Irrotational Vector Fields via a Discretized Ray Transform,
JMIV(52), No. 2, June 2015, pp. 285-302.
Springer DOI 1505
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Boublil, D., Elad, M., Shtok, J., Zibulevsky, M.,
Spatially-Adaptive Reconstruction in Computed Tomography Using Neural Networks,
MedImg(34), No. 7, July 2015, pp. 1474-1485.
IEEE DOI 1507
Artificial neural networks BibRef

Brunetti, S.[Sara], Dulio, P.[Paolo], Hajdu, L.[Lajos], Peri, C.[Carla],
Ghosts in Discrete Tomography,
JMIV(53), No. 2, October 2015, pp. 210-224.
Springer DOI 1508
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Brunetti, S.[Sara], Dulio, P.[Paolo], Peri, C.[Carla],
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Nilchian, M., Ward, J.P., Vonesch, C., Unser, M.,
Optimized Kaiser-Bessel Window Functions for Computed Tomography,
IP(24), No. 11, November 2015, pp. 3826-3833.
IEEE DOI 1509
approximation theory BibRef

Kaganovsky, Y.[Yan], Han, S.B.[Shao-Bo], Degirmenci, S.[Soysal], Politte, D.G.[David G.], Brady, D.J.[David J.], O'Sullivan, J.A.[Joseph A.], Carin, L.[Lawrence],
Alternating Minimization Algorithm with Automatic Relevance Determination for Transmission Tomography under Poisson Noise,
SIIMS(8), No. 3, 2015, pp. 2087-2132.
DOI Link 1511
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Miao, C.[Chuang], Yu, H.Y.[Heng-Yong],
A General-Thresholding Solution for l_p (0< p< 1) Regularized CT Reconstruction,
IP(24), No. 12, December 2015, pp. 5455-5468.
IEEE DOI 1512
compressed sensing BibRef

Grigoryan, A.M.[Artyom M.],
Solution of the Problem on Image Reconstruction in Computed Tomography,
JMIV(54), No. 1, January 2016, pp. 35-63.
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Wu, M., Yoon, S., Solomon, E.G., Star-Lack, J., Pelc, N., Fahrig, R.,
Digital Tomosynthesis System Geometry Analysis Using Convolution-Based Blur-and-Add (BAA) Model,
MedImg(35), No. 1, January 2016, pp. 131-143.
IEEE DOI 1601
Biomedical imaging BibRef

Stille, M., Kleine, M., Hagele, J., Barkhausen, J., Buzug, T.M.,
Augmented Likelihood Image Reconstruction,
MedImg(35), No. 1, January 2016, pp. 158-173.
IEEE DOI 1601
Attenuation BibRef

Chen, Y., O'Sullivan, J.A., Politte, D.G., Evans, J.D., Han, D., Whiting, B.R., Williamson, J.F.,
Line Integral Alternating Minimization Algorithm for Dual-Energy X-Ray CT Image Reconstruction,
MedImg(35), No. 2, February 2016, pp. 685-698.
IEEE DOI 1602
Attenuation BibRef

Kongskov, R.D.[Rasmus Dalgas], Jorgensen, J.S.[Jakob Sauer], Poulsen, H.F.[Henning Friis], Hansen, P.C.[Per Christian],
Noise robustness of a combined phase retrieval and reconstruction method for phase-contrast tomography,
JOSA-A(33), No. 4, April 2016, pp. 447-454.
DOI Link 1604
Mathematical methods in physics BibRef

Kjer, H.M.[Hans Martin], Dong, Y.[Yiqiu], Hansen, P.C.[Per Christian],
User-Friendly Simultaneous Tomographic Reconstruction and Segmentation with Class Priors,
SSVM17(260-270).
Springer DOI 1706
BibRef

Hashemi, S.[Sayed_Masoud], Beheshti, S.[Soosan], Cobbold, R.S.C.[Richard S. C.], Paul, N.S.[Narinder S.],
Subband-dependent compressed sensing in local CT reconstruction,
SIViP(10), No. 6, June 2016, pp. 1009-1015.
Springer DOI 1608
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Liu, J., Ding, H., Molloi, S., Zhang, X., Gao, H.,
TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT,
MedImg(35), No. 12, December 2016, pp. 2578-2586.
IEEE DOI 1612
Attenuation BibRef

Fu, L., Lee, T.C., Kim, S.M., Alessio, A.M., Kinahan, P.E., Chang, Z., Sauer, K., Kalra, M.K., de Man, B.[Bruno],
Comparison Between Pre-Log and Post-Log Statistical Models in Ultra-Low-Dose CT Reconstruction,
MedImg(36), No. 3, March 2017, pp. 707-720.
IEEE DOI 1703
Computational modeling BibRef

Alcaín, E.[Eduardo], Torrado-Carvajal, A.[Angel], Montemayor, A.S.[Antonio S.], Malpica, N.[Norberto],
Real-time patch-based medical image modality propagation by GPU computing,
RealTimeIP(13), No. 1, March 2017, pp. 193-204.
Springer DOI 1704
I.e. create CT like data from MRI and/or PET. BibRef

Gerard, Y.[Yan],
About the Decidability of Polyhedral Separability in the Lattice Zd,
JMIV(59), No. 1, September 2017, pp. 52-68.
Springer DOI 1708
BibRef
Earlier:
About the Complexity of Timetables and 3-Dimensional Discrete Tomography: A Short Proof of NP-Hardness,
IWCIA09(289-301).
Springer DOI 0911
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Wang, Q.[Qian], Zhu, Y.N.[Yi-Ning],
Multi-Domain Regularization Based Computed Tomography for High-Speed Rotation Objects,
SIIMS(10), No. 2, 2017, pp. 602-640.
DOI Link 1708
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McCann, M.T., Unser, M.,
High-Quality Parallel-Ray X-Ray CT Back Projection Using Optimized Interpolation,
IP(26), No. 10, October 2017, pp. 4639-4647.
IEEE DOI 1708
computerised tomography, image filtering, image reconstruction, interpolation, medical image processing, optimisation, analytical phantoms, filtered back projection, forward projections, BibRef

Gang, G.J., Siewerdsen, J.H., Stayman, J.W.,
Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography,
MedImg(36), No. 12, December 2017, pp. 2424-2435.
IEEE DOI 1712
Computed tomography, Image quality, Image reconstruction, Modulation, Optimization, CT, Task-based optimization, model-based reconstruction BibRef

Bai, T., Yan, H., Jia, X., Jiang, S., Wang, G., Mou, X.,
Z-Index Parameterization for Volumetric CT Image Reconstruction via 3-D Dictionary Learning,
MedImg(36), No. 12, December 2017, pp. 2466-2478.
IEEE DOI 1712
Computed tomography, Dictionaries, Image reconstruction, Machine learning, Matching pursuit algorithms, sparse representation BibRef

Gong, H., Li, B., Jia, X., Cao, G.,
Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography,
MedImg(37), No. 2, February 2018, pp. 349-360.
IEEE DOI 1802
Computed tomography, Monte Carlo methods, Phantoms, Scattering, X-ray imaging, Multi-source, cross scattering, forward scattering, scatter correction BibRef

Ha, S., Mueller, K.,
A Look-Up Table-Based Ray Integration Framework for 2-D/3-D Forward and Back Projection in X-Ray CT,
MedImg(37), No. 2, February 2018, pp. 361-371.
IEEE DOI 1802
Computational modeling, Computed tomography, Detectors, Geometry, Table lookup, separable footprint BibRef

Bao, Y.J.[Yi-Jun], Gaylord, T.K.[Thomas K.],
Iterative optimization in tomographic deconvolution phase microscopy,
JOSA-A(35), No. 4, April 2018, pp. 652-660.
DOI Link 1804
Deconvolution, Image reconstruction techniques, Tomographic image processing, Tomography BibRef

Yi, H.[Huangjian], Wei, H.[Hongna], Peng, J.Y.[Jin-Ye], Hou, Y.Q.[Yu-Qing], He, X.W.[Xiao-Wei],
Adaptive threshold method for recovered images of FMT,
JOSA-A(35), No. 2, February 2018, pp. 256-261.
DOI Link 1804
Image processing, Image reconstruction techniques, Medical and biological imaging, Tomography BibRef

Mahmood, F., Shahid, N., Skoglund, U., Vandergheynst, P.,
Adaptive Graph-Based Total Variation for Tomographic Reconstructions,
SPLetters(25), No. 5, May 2018, pp. 700-704.
IEEE DOI 1805
Compressed sensing, Computed tomography, Image reconstruction, Signal processing algorithms, Subspace constraints, TV, Graphs, total variation BibRef

Shen, C., Gonzalez, Y., Chen, L., Jiang, S.B., Jia, X.,
Intelligent Parameter Tuning in Optimization-Based Iterative CT Reconstruction via Deep Reinforcement Learning,
MedImg(37), No. 6, June 2018, pp. 1430-1439.
IEEE DOI 1806
Computed tomography, Image quality, Image reconstruction, Machine learning, Optimization, Radio frequency, Tuning, x-ray imaging BibRef

Würfl, T., Hoffmann, M., Christlein, V., Breininger, K., Huang, Y., Unberath, M., Maier, A.K.,
Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems,
MedImg(37), No. 6, June 2018, pp. 1454-1463.
IEEE DOI 1806
Computed tomography, Geometry, Image reconstruction, Iterative methods, Machine learning, Neural networks, neural networks BibRef

Wang, G., Ye, J.C., Mueller, K., Fessler, J.A.,
Image Reconstruction is a New Frontier of Machine Learning,
MedImg(37), No. 6, June 2018, pp. 1289-1296.
IEEE DOI 1806
Computed tomography, Image reconstruction, Iterative methods, Machine learning, Magnetic resonance imaging BibRef

Adler, J., Öktem, O.,
Learned Primal-Dual Reconstruction,
MedImg(37), No. 6, June 2018, pp. 1322-1332.
IEEE DOI 1806
Computed tomography, Image reconstruction, Inverse problems, Machine learning, TV, Inverse problems, deep learning, optimization, tomography BibRef

Korcyl, G., Bialas, P., Curceanu, C., Czerwinski, E., Dulski, K., Flak, B., Gajos, A., Glowacz, B., Gorgol, M., Hiesmayr, B.C., Jasinska, B., Kacprzak, K., Kajetanowicz, M., Kisielewska, D., Kowalski, P., Kozik, T., Krawczyk, N., Krzemien, W., Kubicz, E., Mohammed, M., Niedzwiecki, S., Pawlik-Niedzwiecka, M., Palka, M., Raczynski, L., Rajda, P., Rudy, Z., Salabura, P., Sharma, N.G., Sharma, S., Shopa, R.Y., Skurzok, M., Silarski, M., Strzempek, P., Wieczorek, A., Wislicki, W., Zaleski, R., Zgardzinska, B., Zielinski, M., Moskal, P.,
Evaluation of Single-Chip, Real-Time Tomographic Data Processing on FPGA SoC Devices,
MedImg(37), No. 11, November 2018, pp. 2526-2535.
IEEE DOI 1811
Image reconstruction, Field programmable gate arrays, Real-time systems, Physics, Detectors, parallel computing BibRef

Zhang, H., Gang, G.J., Dang, H., Stayman, J.W.,
Regularization Analysis and Design for Prior-Image-Based X-Ray CT Reconstruction,
MedImg(37), No. 12, December 2018, pp. 2675-2686.
IEEE DOI 1812
Image reconstruction, Computed tomography, Image quality, X-ray imaging, Current measurement, X-ray CT, regularization design BibRef

Khanin, A., Anton, M., Reginatto, M., Elster, C.,
Assessment of CT Image Quality Using a Bayesian Framework,
MedImg(37), No. 12, December 2018, pp. 2687-2694.
IEEE DOI 1812
Observers, Task analysis, Image quality, Bayes methods, Image reconstruction, Computed tomography, Lesions, Image quality, X-ray tomography BibRef

Webber, J.W.[James W.], Quinto, E.T.[Eric Todd],
Microlocal Analysis of a Compton Tomography Problem,
SIIMS(13), No. 2, 2020, pp. 746-774.
DOI Link 2007
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Purisha, Z., Karhula, S.S., Ketola, J.H., Rimpeläinen, J., Nieminen, M.T., Saarakkala, S., Kröger, H., Siltanen, S.,
An Automatic Regularization Method: An Application for 3-D X-Ray Micro-CT Reconstruction Using Sparse Data,
MedImg(38), No. 2, February 2019, pp. 417-425.
IEEE DOI 1902
Bones, Image reconstruction, Transforms, Computed tomography, X-ray imaging, Biomedical imaging, shearlets BibRef

Li, Y., Chen, G.,
An Empirical Data Inconsistency Metric (DIM) Driven CT Image Reconstruction Method,
MedImg(38), No. 2, February 2019, pp. 337-348.
IEEE DOI 1902
Image reconstruction, X-ray imaging, Computed tomography, Measurement, Data acquisition, Reconstruction algorithms, spectral-inconsistency BibRef

Li, M., Zhao, Y., Zhang, P.,
Accurate Iterative FBP Reconstruction Method for Material Decomposition of Dual Energy CT,
MedImg(38), No. 3, March 2019, pp. 802-812.
IEEE DOI 1903
Image reconstruction, X-ray imaging, Reconstruction algorithms, Iterative methods, Computed tomography, Attenuation, material decomposition BibRef

Wu, W., Liu, F., Zhang, Y., Wang, Q., Yu, H.,
Non-Local Low-Rank Cube-Based Tensor Factorization for Spectral CT Reconstruction,
MedImg(38), No. 4, April 2019, pp. 1079-1093.
IEEE DOI 1904
Tensile stress, Computed tomography, Image reconstruction, Filtering, Detectors, Collaboration, Image edge detection, non-local image similarity BibRef

Zhao, H.K.[Hong-Kai], Zhong, Y.M.[Yi-Min],
A Hybrid Adaptive Phase Space Method for Reflection Traveltime Tomography,
SIIMS(12), No. 1, 2019, pp. 28-53.
DOI Link 1904
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Wei, W.[Wei], Zhou, B.[Bin], Polap, D.[Dawid], Wozniak, M.[Marcin],
A regional adaptive variational PDE model for computed tomography image reconstruction,
PR(92), 2019, pp. 64-81.
Elsevier DOI 1905
Image reconstruction, Combined functional, Partial differential equation, Regional analysis, Variational analysis BibRef

Bappy, D.M., Jeon, I.[Insu],
High-quality X-ray computed tomography reconstruction using projected and interpolated images,
IET-IPR(13), No. 7, 30 May 2019, pp. 1074-1080.
DOI Link 1906
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Abadi, E., Harrawood, B., Sharma, S., Kapadia, A., Segars, W.P., Samei, E.,
DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography,
MedImg(38), No. 6, June 2019, pp. 1457-1465.
IEEE DOI 1906
Detectors, Computed tomography, Computational modeling, Phantoms, Imaging phantoms, Photonics, Virtual clinical trial, simulation, monte carlo BibRef

Li, Y., Li, K., Zhang, C., Montoya, J., Chen, G.,
Learning to Reconstruct Computed Tomography Images Directly From Sinogram Data Under A Variety of Data Acquisition Conditions,
MedImg(38), No. 10, October 2019, pp. 2469-2481.
IEEE DOI 1910
Image reconstruction, Computed tomography, Kernel, Convolution, Training, Deep learning, Image reconstruction, deep learning, interior tomography BibRef

Yeung, T.S.A.[T. S. Au], Chung, E.T.[Eric T.], Uhlmann, G.[Gunther],
Numerical Inversion of Three-Dimensional Geodesic X-Ray Transform Arising from Travel Time Tomography,
SIIMS(12), No. 3, 2019, pp. 1296-1323.
DOI Link 1911
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Du, M.[Ming], Vescovi, R.[Rafael], Fezzaa, K.[Kamel], Jacobsen, C.[Chris], Gursoy, D.[Douga],
X-ray tomography of extended objects: a comparison of data acquisition approaches,
JOSA-A(35), No. 11, November 2018, pp. 1871-1879.
DOI Link 1912
Absorption coefficient, Attenuation coefficient, Image quality, Image registration, Imaging techniques, Light sources BibRef

Ravishankar, S., Ye, J.C., Fessler, J.A.,
Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning,
PIEEE(108), No. 1, January 2020, pp. 86-109.
IEEE DOI 2001
Image reconstruction, Computed tomography, Mathematical model, Magnetic resonance imaging, Machine learning, X-ray imaging, X-ray computed tomography (CT) BibRef

You, C., Li, G., Zhang, Y., Zhang, X., Shan, H., Li, M., Ju, S., Zhao, Z., Zhang, Z., Cong, W., Vannier, M.W., Saha, P.K., Hoffman, E.A., Wang, G.,
CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE),
MedImg(39), No. 1, January 2020, pp. 188-203.
IEEE DOI 2001
Computed tomography, Image resolution, Generative adversarial networks, Image reconstruction, Training, residual learning BibRef

Chang, S., Li, M., Yu, H., Chen, X., Deng, S., Zhang, P., Mou, X.,
Spectrum Estimation-Guided Iterative Reconstruction Algorithm for Dual Energy CT,
MedImg(39), No. 1, January 2020, pp. 246-258.
IEEE DOI 2001
Image reconstruction, Computed tomography, Spectral analysis, X-ray imaging, Attenuation, Reconstruction algorithms, iterative reconstruction BibRef

Balandin, A.L.,
Tomographic Reconstruction of the Beltrami Fields,
JMIV(62), No. 1, January 2020, pp. 1-9.
WWW Link. 2001
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van de Leemput, S.C., Prokop, M., van Ginneken, B., Manniesing, R.,
Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-Contrast CT From Spatiotemporal 4D CT,
MedImg(39), No. 4, April 2020, pp. 985-996.
IEEE DOI 2004
Spatiotemporal phenomena, Computed tomography, Convolution, Biomedical imaging, C-LSTM BibRef

Li, Z., Ravishankar, S., Long, Y., Fessler, J.A.,
DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering,
MedImg(39), No. 4, April 2020, pp. 1223-1234.
IEEE DOI 2004
Transforms, Computed tomography, Computational modeling, Image reconstruction, Attenuation, Matrix decomposition, cross-material models BibRef

Hehn, L., Gradl, R., Dierolf, M., Morgan, K.S., Paganin, D.M., Pfeiffer, F.,
Model-Based Iterative Reconstruction for Propagation-Based Phase-Contrast X-Ray CT including Models for the Source and the Detector,
MedImg(39), No. 6, June 2020, pp. 1975-1987.
IEEE DOI 2006
X-ray imaging and computed tomography, Image reconstruction - iterative methods BibRef

Zeng, D., Yao, L., Ge, Y., Li, S., Xie, Q., Zhang, H., Bian, Z., Zhao, Q., Li, Y., Xu, Z., Meng, D., Ma, J.,
Full-Spectrum-Knowledge-Aware Tensor Model for Energy-Resolved CT Iterative Reconstruction,
MedImg(39), No. 9, September 2020, pp. 2831-2843.
IEEE DOI 2009
Image reconstruction, Tensile stress, Computed tomography, Photonics, Correlation, Detectors, tensor total variation BibRef

Deeba, F.[Farah], Kun, S.[She], Dharejo, F.A.[Fayaz Ali], Zhou, Y.C.[Yuan-Chun],
Sparse representation based computed tomography images reconstruction by coupled dictionary learning algorithm,
IET-IPR(14), No. 11, September 2020, pp. 2365-2375.
DOI Link 2009
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Shi, Y., Gao, Y., Zhang, Y., Sun, J., Mou, X., Liang, Z.,
Spectral CT Reconstruction via Low-Rank Representation and Region-Specific Texture Preserving Markov Random Field Regularization,
MedImg(39), No. 10, October 2020, pp. 2996-3007.
IEEE DOI 2010
Computed tomography, Image reconstruction, Tensors, Correlation, Photonics, Markov random fields, Radiology, texture preservation BibRef

Qian, P.J.[Peng-Jiang], Chen, Y.Y.[Yang-Yang], Kuo, J.W.[Jung-Wen], Zhang, Y.D.[Yu-Dong], Jiang, Y.Z.[Yi-Zhang], Zhao, K.[Kaifa], Helo, R.A.[Rose Al], Friel, H.[Harry], Baydoun, A.[Atallah], Zhou, F.F.[Fei-Fei], Heo, J.U.[Jin Uk], Avril, N.[Norbert], Herrmann, K.[Karin], Ellis, R.[Rodney], Traughber, B.[Bryan], Jones, R.S.[Robert S.], Wang, S.T.[Shi-Tong], Su, K.H.[Kuan-Hao], Muzic, R.F.[Raymond F.],
mDixon-Based Synthetic CT Generation for PET Attenuation Correction on Abdomen and Pelvis Jointly Using Transfer Fuzzy Clustering and Active Learning-Based Classification,
MedImg(39), No. 4, April 2020, pp. 819-832.
IEEE DOI 2004
Synthetic CT generation, Dixon-based MR, abdomen, attenuation correction (AC), transfer fuzzy clustering (TFC), active learning-based classification (ALC) BibRef

Song, X.[Xin], Qian, P.J.[Peng-Jiang], Zheng, J.M.[Jia-Min], Jiang, Y.Z.[Yi-Zhang], Xia, K.J.[Kai-Jian], Traughber, B.[Bryan], Wu, D.R.[Dong-Rui], Muzic, R.F.[Raymond F.],
mDixon-based synthetic CT generation via transfer and patch learning,
PRL(138), 2020, pp. 51-59.
Elsevier DOI 1806
Synthetic CT, mDixon MR, Abdomen, Transfer learning, Patch learning BibRef

Ji, X., Zhang, R., Li, K., Chen, G.H.,
Dual Energy Differential Phase Contrast CT (DE-DPC-CT) Imaging,
MedImg(39), No. 11, November 2020, pp. 3278-3289.
IEEE DOI 2011
Computed tomography, Gratings, Iodine, X-ray imaging, Attenuation, Biomedical imaging, Phase contrast imaging, dual energy CT BibRef

Santos, T.B.R., Nakanishi, R.M., Kaipio, J.P., Mueller, J.L., Lima, R.G.,
Introduction of Sample Based Prior into the D-Bar Method Through a Schur Complement Property,
MedImg(39), No. 12, December 2020, pp. 4085-4093.
IEEE DOI 2012
Conductivity, Image reconstruction, Tomography, Voltage measurement, Mathematical model, Computational modeling, prior information BibRef

Zhang, T., Zhang, L., Chen, Z., Xing, Y., Gao, H.,
Fourier Properties of Symmetric-Geometry Computed Tomography and Its Linogram Reconstruction With Neural Network,
MedImg(39), No. 12, December 2020, pp. 4445-4457.
IEEE DOI 2012
Computed tomography, Image reconstruction, Fourier transforms, Detectors, Neural networks, Geometry, neural network BibRef

Vent, T.L.[Trevor Lewis], Acciavatti, R.J.[Raymond Joseph], Maidment, A.D.A.[Andrew D. A.],
Development and Evaluation of the Fourier Spectral Distortion Metric,
MedImg(40), No. 3, March 2021, pp. 1055-1064.
IEEE DOI 2103
Image reconstruction, Biomedical imaging, Spatial resolution, super resolution BibRef

Ryu, D.H.[Dong-Hun], Ryu, D.M.[Dong-Min], Baek, Y.S.[Yoon-Seok], Cho, H.J.[Hyung-Joo], Kim, G.[Geon], Kim, Y.S.[Young Seo], Lee, Y.[Yongki], Kim, Y.[Yoosik], Ye, J.C.[Jong Chul], Min, H.S.[Hyun-Seok], Park, Y.K.[Yong-Keun],
DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging Using Deep Learning,
MedImg(40), No. 5, May 2021, pp. 1508-1518.
IEEE DOI 2105
Computer architecture, Optical diffraction, Microprocessors, Optical imaging, Imaging, deep learning BibRef

Cueva, E.[Evelyn], Meaney, A.[Alexander], Siltanen, S.[Samuli], Ehrhardt, M.J.[Matthias J.],
Synergistic Multi-Spectral CT Reconstruction with Directional Total Variation,
Royal(A: 379), No. 2204, August 2021, pp. 20200198.
DOI Link 2107

See also Multicontrast MRI Reconstruction with Structure-Guided Total Variation. BibRef

Ito, S.[Shota], Toda, N.[Naohiro],
Improvement of CT Reconstruction Using Scattered X-Rays,
IEICE(E104-D), No. 8, August 2021, pp. 1378-1385.
WWW Link. 2108
BibRef

Zhang, S.[Shu], Xia, Y.[Youshen],
4D computed tomography super-resolution reconstruction based on tensor product and nuclear norm optimization,
PR(121), 2022, pp. 108150.
Elsevier DOI 2109
4D-CT, Super-resolution, Tensor product, Optimization, Nuclear norm BibRef

Park, H.S.[Hyoung Suk], Jung, J.[Junhwa], Seo, J.K.[Jin Keun],
Pseudo-monochromatic Imaging in Industrial X-Ray Computed Tomography,
SIIMS(14), No. 3, 2021, pp. 1306-1325.
DOI Link 2110
BibRef

Bhadra, S.[Sayantan], Kelkar, V.A.[Varun A.], Brooks, F.J.[Frank J.], Anastasio, M.A.[Mark A.],
On Hallucinations in Tomographic Image Reconstruction,
MedImg(40), No. 11, November 2021, pp. 3249-3260.
IEEE DOI 2111
Image reconstruction, Imaging, Reconstruction algorithms, Noise measurement, Training, Null space, Superresolution, hallucinations BibRef

Tao, X.[Xi], Wang, Y.B.[Yong-Bo], Lin, L.Y.[Li-Yan], Hong, Z.X.[Zi-Xuan], Ma, J.H.[Jian-Hua],
Learning to Reconstruct CT Images From the VVBP-Tensor,
MedImg(40), No. 11, November 2021, pp. 3030-3041.
IEEE DOI 2111
Image reconstruction, Computed tomography, Tensors, Sorting, Training, Image coding, Biomedical imaging, Computed tomography, VVBP-Tensor BibRef

Yang, S.[Serin], Kim, E.Y.[Eung Yeop], Ye, J.C.[Jong Chul],
Continuous Conversion of CT Kernel Using Switchable CycleGAN With AdaIN,
MedImg(40), No. 11, November 2021, pp. 3015-3029.
IEEE DOI 2111
Kernel, Computed tomography, Generators, Switches, Image reconstruction, Interpolation, Deep learning, adaptive instance normalization (AdaIN) BibRef

Ye, S.Q.[Si-Qi], Li, Z.P.[Zhi-Peng], McCann, M.T.[Michael T.], Long, Y.[Yong], Ravishankar, S.[Saiprasad],
Unified Supervised-Unsupervised (SUPER) Learning for X-Ray CT Image Reconstruction,
MedImg(40), No. 11, November 2021, pp. 2986-3001.
IEEE DOI 2111
Image reconstruction, Computed tomography, Training, Transforms, Imaging, X-ray imaging, Iterative methods, Low-dose X-ray CT, bilevel optimization BibRef

He, J.[Ji], Chen, S.L.[Shi-Lin], Zhang, H.[Hua], Tao, X.[Xi], Lin, W.[Wuhong], Zhang, S.[Shanli], Zeng, D.[Dong], Ma, J.H.[Jian-Hua],
Downsampled Imaging Geometric Modeling for Accurate CT Reconstruction via Deep Learning,
MedImg(40), No. 11, November 2021, pp. 2976-2985.
IEEE DOI 2111
Computed tomography, Image reconstruction, Imaging, Computational modeling, Detectors, Neural networks, Data models, deep learning BibRef

An, Y.[Yu], Bian, C.[Chang], Yan, D.X.[Da-Xiang], Wang, H.[Hanfan], Wang, Y.[Yu], Du, Y.[Yang], Tian, J.[Jie],
A Fast and Automated FMT/XCT Reconstruction Strategy Based on Standardized Imaging Space,
MedImg(41), No. 3, March 2022, pp. 657-666.
IEEE DOI 2203
Imaging, Image reconstruction, Mice, In vivo, Image segmentation, Finite element analysis, Surface reconstruction, standardized imaging space BibRef

He, Y.T.[Yu-Tao], Ming, W.Q.[Wen-Quan], Shen, R.H.[Ruo-Han], Chen, J.H.[Jiang-Hua],
IDART: An Improved Discrete Tomography Algorithm for Reconstructing Images With Multiple Gray Levels,
IP(31), 2022, pp. 2608-2619.
IEEE DOI 2204
Computed tomography, Morphology, Phantoms, Reconstruction algorithms, Noise measurement, Labeling, missing wedge BibRef

Savanier, M.[Marion], Chouzenoux, E.[Emilie], Pesquet, J.C.[Jean-Christophe], Riddell, C.[Cyril],
Unmatched Preconditioning of the Proximal Gradient Algorithm,
SPLetters(29), 2022, pp. 1122-1126.
IEEE DOI 2205
Electronics packaging, Convergence, Measurement, Linear programming, Standards, Signal processing algorithms, proximal methods BibRef

Hu, D.L.[Dian-Lin], Zhang, Y.K.[Yi-Kun], Liu, J.[Jin], Luo, S.H.[Shou-Hua], Chen, Y.[Yang],
DIOR: Deep Iterative Optimization-Based Residual-Learning for Limited-Angle CT Reconstruction,
MedImg(41), No. 7, July 2022, pp. 1778-1790.
IEEE DOI 2207
Image reconstruction, Computed tomography, Image edge detection, TV, Reconstruction algorithms, Optimization, Deep learning, perceptual loss BibRef

Ma, B.X.[Bo-Xiao], Zalmai, N.[Nour], Loeliger, H.A.[Hans-Andrea],
Smoothed-NUV Priors for Imaging,
IP(31), 2022, pp. 4663-4678.
IEEE DOI 2207
Normal priors with Unknown Variance (NUV). TV, Image reconstruction, Minimization, Image edge detection, Iterative algorithms, Image segmentation, Tensors, image segmentation BibRef

Chen, X.[Xiang], Xia, W.J.[Wen-Jun], Liu, Y.[Yan], Chen, H.[Hu], Zhou, J.L.[Ji-Liu], Zha, Z.Y.[Zhi-Yuan], Wen, B.H.[Bi-Han], Zhang, Y.[Yi],
FONT-SIR: Fourth-Order Nonlocal Tensor Decomposition Model for Spectral CT Image Reconstruction,
MedImg(41), No. 8, August 2022, pp. 2144-2156.
IEEE DOI 2208
Tensors, Computed tomography, Image reconstruction, Photonics, Correlation, X-ray imaging, Principal component analysis, nuclear norm BibRef

Rudzusika, J.[Jevgenija], Koehler, T.[Thomas], Oktem, O.[Ozan],
Deep Learning: Based Dictionary Learning and Tomographic Image Reconstruction,
SIIMS(15), No. 4, 2022, pp. 1729-1764.
DOI Link 2211
BibRef

Tao, W.J.[Wei-Jie], Rohmer, D.[Damien], Gullberg, G.T.[Grant T.], Seo, Y.[Youngho], Huang, Q.[Qiu],
An Analytical Algorithm for Tensor Tomography From Projections Acquired About Three Axes,
MedImg(41), No. 11, November 2022, pp. 3454-3472.
IEEE DOI 2211
Tensors, Image reconstruction, X-ray imaging, Ellipsoids, Filtering algorithms, Biomedical measurement, directional X-ray projections BibRef

Li, D.Y.[Dan-Yang], Bian, Z.Y.[Zhao-Ying], Li, S.[Sui], He, J.[Ji], Zeng, D.[Dong], Ma, J.H.[Jian-Hua],
Noise Characteristics Modeled Unsupervised Network for Robust CT Image Reconstruction,
MedImg(41), No. 12, December 2022, pp. 3849-3861.
IEEE DOI 2212
Computed tomography, Perturbation methods, Protocols, Training, Image reconstruction, Testing, Reconstruction algorithms, CT, Gaussian mixture model BibRef

Lukic, T.[Tibor], Kopanja, T.[Tamara],
Tomography Reconstruction Based on Null Space Search,
IWCIA22(247-259).
Springer DOI 2301
BibRef

Schmid, C.[Clemens], Viermetz, M.[Manuel], Gustschin, N.[Nikolai], Noichl, W.[Wolfgang], Haeusele, J.[Jakob], Lasser, T.[Tobias], Koehler, T.[Thomas], Pfeiffer, F.[Franz],
Modeling Vibrations of a Tiled Talbot-Lau Interferometer on a Clinical CT,
MedImg(42), No. 3, March 2023, pp. 774-784.
IEEE DOI 2303
Gratings, Vibrations, Fluctuations, Detectors, X-ray imaging, Computed tomography, Optimization, Dimensionality reduction, X-ray imaging and computed tomography BibRef

Li, Y.H.[Yun-He], Chen, L.[Lunqiang], Li, B.[Bo], Zhao, H.[Huiyan],
4× Super-resolution of unsupervised CT images based on GAN,
IET-IPR(17), No. 8, 2023, pp. 2362-2374.
DOI Link 2306
computed tomography images, generative adversarial network, super-resolution BibRef

Bevilacqua, F.[Francesca], Dong, Y.Q.[Yi-Qiu], Jřrgensen, J.S.[Jakob Sauer],
Regularized Material Decomposition for K-edge Separation in Hyperspectral Computed Tomography,
SSVM23(107-119).
Springer DOI 2307
BibRef

Huang, S.[Shuai], Zehni, M.[Mona], Dokmanic, I.[Ivan], Zhao, Z.Z.[Zhi-Zhen],
Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown View Tomography,
SIIMS(16), No. 3, 2023, pp. 1398-1439.
DOI Link 2309
BibRef

Xing, X.D.[Xiao-Dan], Papanastasiou, G.[Giorgos], Walsh, S.[Simon], Yang, G.[Guang],
Less Is More: Unsupervised Mask-Guided Annotated CT Image Synthesis With Minimum Manual Segmentations,
MedImg(42), No. 9, September 2023, pp. 2566-2576.
IEEE DOI 2310
BibRef

Haeusele, J.[Jakob], Schmid, C.[Clemens], Viermetz, M.[Manuel], Gustschin, N.[Nikolai], Lasser, T.[Tobias], Koehler, T.[Thomas], Pfeiffer, F.[Franz],
Advanced Phase-Retrieval for Stepping-Free X-Ray Dark-Field Computed Tomography,
MedImg(42), No. 10, October 2023, pp. 2876-2885.
IEEE DOI 2310
BibRef

Zhang, K.[Kai], Entezari, A.[Alireza],
Convolutional Forward Models for X-Ray Computed Tomography,
SIIMS(16), No. 4, 2023, pp. 1953-1977.
DOI Link 2312
BibRef

Acciavatti, R.J.[Raymond J.], Choi, C.J.[Chloe J.], Vent, T.L.[Trevor L.], Barufaldi, B.[Bruno], Cohen, E.A.[Eric A.], Wileyto, E.P.[E. Paul], Maidment, A.D.A.[Andrew D. A.],
Non-Isocentric Geometry for Next-Generation Tomosynthesis With Super-Resolution,
MedImg(43), No. 1, January 2024, pp. 377-391.
IEEE DOI 2401
BibRef

Pan, J.Y.[Jia-Yi], Yu, H.Y.[Heng-Yong], Gao, Z.[Zhifan], Wang, S.[Shaoyu], Zhang, H.[Heye], Wu, W.W.[Wei-Wen],
Iterative Residual Optimization Network for Limited-Angle Tomographic Reconstruction,
IP(33), 2024, pp. 910-925.
IEEE DOI 2402
Convolution, Reconstruction algorithms, Transformers, Iron, Iterative methods, Image reconstruction, Optimization, convergence BibRef

Cheng, C.C.[Chang-Chieh],
Image representation and reconstruction by compositing Gaussian ellipses,
IET-IPR(18), No. 2, 2024, pp. 493-506.
DOI Link 2402
computerised tomography, gradient methods, image reconstruction, image representation, rendering (computer graphics) BibRef

van Gogh, S.[Stefano], Mukherjee, S.[Subhadip], Rawlik, M.[Michal], Pereira, A.[Alexandre], Spindler, S.[Simon], Zdora, M.C.[Marie-Christine], Stauber, M.[Martin], Varga, Z.[Zsuzsanna], Stampanoni, M.[Marco],
Data-Driven Gradient Regularization for Quasi-Newton Optimization in Iterative Grating Interferometry CT Reconstruction,
MedImg(43), No. 3, March 2024, pp. 1033-1044.
IEEE DOI 2403
Image reconstruction, Computed tomography, Gratings, Noise reduction, Optimization, Interferometry, Scattering, tomography BibRef


Liu, J.M.[Jia-Ming], Anirudh, R.[Rushil], Thiagarajan, J.J.[Jayaraman J.], He, S.[Stewart], Mohan, K.A.[K. Aditya], Kamilov, U.S.[Ulugbek S.], Kim, H.[Hyojin],
DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction,
ICCV23(10464-10474)
IEEE DOI 2401
BibRef

Hamoud, B.[Bassel], Bahat, Y.[Yuval], Michaeli, T.[Tomer],
Beyond Local Processing: Adapting CNNs for CT Reconstruction,
MCV22(513-526).
Springer DOI 2304
BibRef

Ziabari, A.[Amirkoushyar], Venkatakrishnan, S.[Singanallur], Dubey, A.[Abhishek], Lisovich, A.[Alex], Brackman, P.[Paul], Frederick, C.[Curtis], Bhattad, P.[Pradeep], Bingham, P.[Philip], Plotkowski, A.[Alex], Dehoff, R.[Ryan], Paquit, V.[Vincent],
Simurgh: A Framework for CAD-Driven Deep Learning Based X-Ray CT Reconstruction,
ICIP22(3836-3867)
IEEE DOI 2211
Deep learning, Solid modeling, Design automation, Computed tomography, Computational modeling, Neural networks, Metal Additive Manufacturing (AM) BibRef

Schock, J.[Justus], Lan, Y.C.[Yu-Chia], Truhn, D.[Daniel], Kopaczka, M.[Marcin], Conrad, S.[Stefan], Nebelung, S.[Sven], Merhof, D.[Dorit],
Monoplanar CT Reconstruction with GANs,
IPTA22(1-6)
IEEE DOI 2206
Radiography, Training, Image analysis, Databases, Computed tomography, Data visualization, Prediction methods, CT, deeplearning BibRef

Sde-Chen, Y.[Yael], Schechner, Y.Y.[Yoav Y.], Holodovsky, V.[Vadim], Eytan, E.[Eshkol],
3DeepCT: Learning Volumetric Scattering Tomography of Clouds,
ICCV21(5651-5662)
IEEE DOI 2203
Inverse problems, Computational modeling, Clouds, Atmospheric modeling, Scattering, Signal processing, Stereo, Vision applications and systems BibRef

Zang, G.M.[Guang-Ming], Idoughi, R.[Ramzi], Li, R.[Rui], Wonka, P.[Peter], Heidrich, W.[Wolfgang],
IntraTomo: Self-supervised Learning-based Tomography via Sinogram Synthesis and Prediction,
ICCV21(1940-1950)
IEEE DOI 2203
Geometry, Deep learning, Inverse problems, Computed tomography, Computational modeling, Superresolution, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Jantre, S.R.[Sanket R.], Di, Z.W.[Zichao Wendy],
Low-Rank Tensor Regression for X-Ray Tomography,
ICIP21(2833-2837)
IEEE DOI 2201
Tensors, Inverse problems, X-ray tomography, Reconstruction algorithms, Robustness, inverse problem, low-rank approximation BibRef

Yang, X.G.[Xiao-Gang], Schroer, C.[Christian],
Strategies of Deep Learning for Tomographic Reconstruction,
ICIP21(3473-3476)
IEEE DOI 2201
Deep learning, Simulation, Software algorithms, Phantoms, Tomography, Generative adversarial networks, Cost function, Deep learning, Tomographic Reconstruction BibRef

Balke, T.[Thilo], Long, A.M.[Alexander M.], Vogel, S.C.[Sven C.], Wohlberg, B.[Brendt], Bouman, C.A.[Charles A.],
Hyperspectral Neutron CT with Material Decomposition,
ICIP21(3482-3486)
IEEE DOI 2201
Radiography, Image coding, Neutrons, Tools, Linear programming, Image sequences, Noise measurement, neutron imaging, material decomposition BibRef

Wedekind, M.[Markus], Oertel, E.[Eric], Castillo, S.[Susana], Magnor, M.[Marcus],
Reducing Stair Artifacts in CT Reconstruction,
ICIP21(3492-3496)
IEEE DOI 2201
Radiography, Surface reconstruction, Computed tomography, Stairs, Filtering algorithms, Information filters, aliasing, stair artifacts BibRef

Plier, J.[Jan], Savarino, F.[Fabrizio], Kocvara, M.[Michal], Petra, S.[Stefania],
First-order Geometric Multilevel Optimization for Discrete Tomography,
SSVM21(191-203).
Springer DOI 2106
BibRef

Zhao, H.[Huan], Wang, Y.[Yu], Li, T.T.[Ting-Ting], Zhao, Y.Q.[Yu-Qing],
An Asymmetric Two-sided Penalty Term for CT-GAN,
MMMod21(I:11-23).
Springer DOI 2106
BibRef

Paramonov, P., Lumbeeck, L.P., Beenhouwer, J.D., Sijbers, J.,
Accurate Terahertz Imaging Simulation With Ray Tracing Incorporating Beam Shape and Refraction,
ICIP20(3035-3039)
IEEE DOI 2011
Shape, Physics, Refractive index, Computed tomography, Ray tracing, Geometry, Terahertz imaging, computed tomography, ray tracing, forward projection BibRef

Six, N., Renders, J., Sijbers, J., Beenhouwer, J.D.,
Newton-Krylov Methods For Polychromatic X-Ray CT,
ICIP20(3045-3049)
IEEE DOI 2011
Image reconstruction, Mathematical model, Jacobian matrices, Computed tomography, Linear programming, Attenuation, Newton-Krylov BibRef

Zhao, Q., Ma, X., Cuadros, A., Arce, G.R., Chen, R.,
Non-Linear 3d Reconstruction For Compressive X-Ray Tomosynthesis,
ICIP20(3149-3153)
IEEE DOI 2011
Image reconstruction, X-ray imaging, Detectors, Biomedical imaging, Encoding, X-ray tomosynthesis, coding mask BibRef

Lékó, G.[Gábor], Balázs, P.[Péter],
Transmission Based Adaptive Automatic Tube Voltage Selection for Computed Tomography,
IWCIA20(199-208).
Springer DOI 2009
BibRef

Moeller, M., Moellenhoff, T., Cremers, D.,
Controlling Neural Networks via Energy Dissipation,
ICCV19(3255-3264)
IEEE DOI 2004
computerised tomography, gradient methods, image reconstruction, image resolution, image restoration, Iterative methods BibRef

Ghani, M.U., Karl, W.C.,
Integrating Data and Image Domain Deep Learning for Limited Angle Tomography using Consensus Equilibrium,
CLI19(3922-3932)
IEEE DOI 2004
computerised tomography, image reconstruction, learning (artificial intelligence), medical image processing, Image Domain Learning BibRef

Ying, X.D.[Xing-De], Guo, H.[Heng], Ma, K.[Kai], Wu, J.[Jian], Weng, Z.X.[Zheng-Xin], Zheng, Y.F.[Ye-Feng],
X2CT-GAN: Reconstructing CT From Biplanar X-Rays With Generative Adversarial Networks,
CVPR19(10611-10620).
IEEE DOI 2002
BibRef

Unterberger, A., Menser, J., Kempf, A., Mohri, K.,
Evolutionary Camera Pose Estimation of a Multi-Camera Setup for Computed Tomography,
ICIP19(464-468)
IEEE DOI 1910
Camera Calibration, Genetic Algorithm, Ray-Tracing, Computed Tomography BibRef

Yoo, S., Yang, X., Wolfman, M., Gursoy, D., Katsaggelos, A.K.,
Sinogram Image Completion for Limited Angle Tomography With Generative Adversarial Networks,
ICIP19(1252-1256)
IEEE DOI 1910
Limited angle tomography, sinogram image completion, deep convolutional generative adversarial networks BibRef

Huang, X., Wild, S.M., Di, Z.W.,
Calibrating Sensing Drift in Tomographic Inversion,
ICIP19(1267-1271)
IEEE DOI 1910
tomography, inverse problem, error calibration, compressive sensing BibRef

Riis, N.A.B.[Nicolai André Brogaard], Dong, Y.[Yiqiu],
A New Iterative Method for CT Reconstruction with Uncertain View Angles,
SSVM19(156-167).
Springer DOI 1909
BibRef

Huo, L.[Limei], Luo, S.[Shousheng], Dong, Y.[Yiqiu], Tai, X.C.[Xue-Cheng], Wang, Y.[Yang],
An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data,
SSVM19(144-155).
Springer DOI 1909
BibRef

Anirudh, R., Kim, H., Thiagarajan, J.J., Mohan, K.A., Champley, K., Bremer, T.,
Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion,
CVPR18(6343-6352)
IEEE DOI 1812
Image reconstruction, Computed tomography, X-ray imaging, Detectors, Training, Transforms BibRef

Geva, A.[Adam], Schechner, Y.Y.[Yoav Y.], Chernyak, Y.[Yonatan], Gupta, R.[Rajiv],
X-Ray Computed Tomography Through Scatter,
ECCV18(XIV: 37-54).
Springer DOI 1810
BibRef

Zang, G.M.[Guang-Ming], Aly, M.[Mohamed], Idoughi, R.[Ramzi], Wonka, P.[Peter], Heidrich, W.[Wolfgang],
Super-Resolution and Sparse View CT Reconstruction,
ECCV18(XVI: 145-161).
Springer DOI 1810
BibRef

Skau, E., Garcia-Cardona, C.,
Tomographic Reconstruction Via 3D Convolutional Dictionary Learning,
IVMSP18(1-5)
IEEE DOI 1809
Convolution, Machine learning, Tomography, Image reconstruction, Signal reconstruction, Kernel, Dictionaries, Tomography, ADMM BibRef

Song, H., Eramian, M., Hallin, E., Leyeza, B., Arnison, P.G., Rogge, R.,
Robust and User Friendly 3D Re-Construction of Neutron Tomographic Images,
WACV18(930-938)
IEEE DOI 1806
biological tissues, image denoising, image reconstruction, impulse noise, medical image processing, neutron radiography, BibRef

Gopal, P., Chaudhry, R., Chandran, S., Svalbe, I., Rajwade, A.,
Tomographic Reconstruction Using Global Statistical Priors,
DICTA17(1-8)
IEEE DOI 1804
compressed sensing, eigenvalues and eigenfunctions, image reconstruction, image representation, iterative methods, BibRef

Dumitru, M., Wang, L., Gac, N., Mohammad-Djafari, A.,
Performance comparison of Bayesian iterative algorithms for three classes of sparsity enforcing priors with application in computed tomography,
ICIP17(3580-3584)
IEEE DOI 1803
Bayes methods, Computational modeling, Computed tomography, Image reconstruction, Phantoms, sparsity enforcing priors BibRef

Svalbe, I.[Imants], Ceko, M.[Matthew],
Maximal N-Ghosts and Minimal Information Recovery from N Projected Views of an Array,
DGCI17(135-146).
Springer DOI 1711
BibRef

Dong, G.Z.[Guo-Zhi], Scherzer, O.[Otmar],
Nonlinear Flows for Displacement Correction and Applications in Tomography,
SSVM17(283-294).
Springer DOI 1706
BibRef

Klodt, M.[Maria], Hauser, R.[Raphael],
3D Image Reconstruction from X-Ray Measurements with Overlap,
ECCV16(VI: 19-33).
Springer DOI 1611
BibRef

Kuske, J.[Jan], Swoboda, P.[Paul], Petra, S.[Stefania],
A Novel Convex Relaxation for Non-binary Discrete Tomography,
SSVM17(235-246).
Springer DOI 1706
BibRef

Zisler, M.[Matthias], Ĺström, F.[Freddie], Petra, S.[Stefania], Schnörr, C.[Christoph],
Image Reconstruction by Multilabel Propagation,
SSVM17(247-259).
Springer DOI 1706
BibRef

Zisler, M.[Matthias], Savarino, F.[Fabrizio], Petra, S.[Stefania], Schnörr, C.[Christoph],
Gradient Flows on a Riemannian Submanifold for Discrete Tomography,
GCPR17(294-305).
Springer DOI 1711
BibRef

Zisler, M.[Matthias], Petra, S.[Stefania], Schnörr, C.[Claudius], Schnörr, C.[Christoph],
Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints,
GCPR16(261-272).
Springer DOI 1611
BibRef

Kappes, J.H.[Jörg Hendrik], Petra, S.[Stefania], Schnörr, C.[Christoph], Zisler, M.[Matthias],
TomoGC: Binary Tomography by Constrained GraphCuts,
GCPR15(262-273).
Springer DOI 1511
BibRef

Sadiq, M.U.[Muhammad Usman], Simmons, J.P.[Jeff. P.], Bouman, C.A.[Charles A.],
Model based image reconstruction with physics based priors,
ICIP16(3176-3179)
IEEE DOI 1610
Computational modeling BibRef

Tuysuzoglu, A., Khoo, Y., Karl, W.C.,
Variable splitting techniques for discrete tomography,
ICIP16(1764-1768)
IEEE DOI 1610
Additives BibRef

Yazdanpanah, A.P.[Ali Pour], Regentova, E.E.[Emma E.],
Sparse-View CT Reconstruction Using Curvelet and TV-Based Regularization,
ICIAR16(672-677).
Springer DOI 1608
BibRef

Brlek, S.[Srecko], Frosini, A.[Andrea],
A Tomographical Interpretation of a Sufficient Condition on h-Graphical Sequences,
DGCI16(95-104).
WWW Link. 1606
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Karimi, D.[Davood], Ward, R.[Rabab],
Interpolation of CT Projections by Exploiting Their Self-Similarity and Smoothness,
ICIP21(165-169)
IEEE DOI 2201
Image quality, Interpolation, Computed tomography, Noise reduction, Detectors, Reconstruction algorithms, denoising BibRef

Karimi, D.[Davood], Ward, R.[Rabab], Ford, N.[Nancy],
Angular upsampling of projection measurements in 3D computed tomography using a sparsity prior,
ICIP15(3363-3367)
IEEE DOI 1512
computed tomography; inpainting; sinogram; sparse modeling; upsampling BibRef

Brandao dos Santos, L.C.[Lilian Chaves], Gouillart, E.[Emmanuelle], Talbot, H.[Hugues],
Combining interior tomography reconstruction and spatial regularization,
ICIP14(1768-1772)
IEEE DOI 1502
Biomedical imaging BibRef

Saha, S.K., Tahtali, M., Lambert, A., Pickering, M.,
Effect of Smoothing on Sparsity Prior CT Reconstruction,
DICTA14(1-8)
IEEE DOI 1502
computerised tomography BibRef

Dhou, S.[Salam], Hugo, G.D.[Geoffrey D.], Docef, A.[Alen],
Motion-based projection generation for 4D-CT reconstruction,
ICIP14(1698-1702)
IEEE DOI 1502
Computed tomography BibRef

Sakhaee, E.[Elham], Entezari, A.[Alireza],
Learning Splines for Sparse Tomographic Reconstruction,
ISVC14(I: 1-10).
Springer DOI 1501
BibRef

Bilotta, S.[Stefano], Brocchi, S.[Stefano],
Discrete Tomography Reconstruction Algorithms for Images with a Blocking Component,
DGCI14(250-261).
Springer DOI 1410
BibRef

van Leeuwen, T.[Tristan], Batenburg, K.J.[K. Joost],
Adaptive Grid Refinement for Discrete Tomography,
DGCI14(297-308).
Springer DOI 1410
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Ouaddah, A.[Ahlem], Boughaci, D.[Dalila],
A New Method to Improve Quality of Reconstructed Images in Tomography,
CompIMAGE14(267-272).
Springer DOI 1407
BibRef

Cengiz, K.[Kubra], Kamasak, M.[Mustafa],
Comparison of algebraic reconstruction techniques for tomosynthesis,
WSSIP14(15-18) 1406
Detectors BibRef

Chouzenoux, E.[Emilie], Zolyniak, F.[Fiona], Gouillart, E.[Emmanuelle], Talbot, H.[Hugues],
A majorize-minimize memory gradient algorithm applied to X-ray tomography,
ICIP13(1011-1015)
IEEE DOI 1402
Detectors BibRef

Brunetti, S.[Sara], Dulio, P.[Paolo], Peri, C.[Carla],
Non-additive Bounded Sets of Uniqueness in Z_n,
DGCI14(226-237).
Springer DOI 1410
BibRef
Earlier:
On the Non-additive Sets of Uniqueness in a Finite Grid,
DGCI13(288-299).
Springer DOI 1304
BibRef

Brandt, S.S.[Sami S.], Jensen, K.H.[Katrine Hommelhoff], Lauze, F.[François],
Bayesian Epipolar Geometry Estimation from Tomographic Projections,
ACCV12(IV:231-242).
Springer DOI 1304
BibRef

Hirsch, M.[Michael], Hofmann, M.[Matthias], Mantlik, F.[Frederic], Pichler, B.J.[Bernd J.], Scholkopf, B.[Bernhard], Habeck, M.[Michael],
A blind deconvolution approach for pseudo CT prediction from MR image pairs,
ICIP12(2953-2956).
IEEE DOI 1302
BibRef

Opie, A.M.T., Bones, P.J.,
Sensitivity to error of the truncated Hilbert transform technique for interior reconstruction,
ICIP11(421-424).
IEEE DOI 1201
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Peyrin, F.[Frangoise], Pacureanu, A.[Alexandra], Langer, M.[Max],
3D microscopic imaging by synchrotron radiation micro/nano-CT,
ICIP11(3057-3060).
IEEE DOI 1201
BibRef

Jang, K.E.[Kwang Eun], Kang, D.G.[Dong-Goo], Han, S.M.[Seok-Min], Lee, K.[Kangeui], Lee, J.H.[Jong-Ha], Sung, Y.H.[Young-Hun],
Regularized polychromatic reconstruction for transmission tomography,
ICIP11(1369-1372).
IEEE DOI 1201
BibRef

Lukic, T.[Tibor],
Discrete Tomography Reconstruction Based on the Multi-well Potential,
IWCIA11(335-345).
Springer DOI 1105
BibRef

Lin, Y.T.[Yen-Ting], Ortega, A.[Antonio], Dimakis, A.G.[Alexandros G.],
Sparse recovery for discrete tomography,
ICIP10(4181-4184).
IEEE DOI 1009
BibRef

Ouksili, Z., Batatia, H.,
4D CT image reconstruction based on interpolated optical flow fields,
ICIP10(633-636).
IEEE DOI 1009
BibRef

Gurov, I.[Igor], Potapov, A.[Alexey],
Investigation of OCT Images Descriptions on the Base of Representational MDL Principle,
MVA09(320-).
PDF File. 0905
OCT: Optical Coherence Tomography BibRef

Recur, B., Desbarats, P., Domenger, J.P.,
Mojette reconstruction from noisy projections,
IPTA10(201-206).
IEEE DOI 1007
BibRef

Westfeld, P., Maas, H.G.,
3D Least Squares Tracking in Time-resolved Tomographic Reconstructions of Dense Flow Marker Particle Fields,
CloseRange10(xx-yy).
PDF File. 1006
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Nagy, A.[Antal],
Smoothing Filters in the DART Algorithm,
IWCIA14(224-237).
Springer DOI 1405
Discrete Algebraic Reconstruction Technique (DART). BibRef

Varga, L.[László], Ozsvár, Z.[Zoltán], Balázs, P.[Péter],
Image Enhancement by Volume Limitation in Binary Tomography,
ISVC16(I: 213-222).
Springer DOI 1701
BibRef

Varga, L.[László], Balázs, P.[Péter], Nagy, A.[Antal],
Projection Selection Algorithms for Discrete Tomography,
ACIVS10(I: 390-401).
Springer DOI 1012
BibRef
And:
Direction-Dependency of a Binary Tomographic Reconstruction Algorithm,
CompIMAGE10(242-253).
Springer DOI 1006
BibRef

Frey, S.[Steffen], Müller, C.[Christoph], Strengert, M.[Magnus], Ertl, T.[Thomas],
Concurrent CT Reconstruction and Visual Analysis Using Hybrid Multi-resolution Raycasting in a Cluster Environment,
ISVC09(I: 357-366).
Springer DOI 0911
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Pribil, J., Zat'ko, B., Frollo, I., Dubecky, F., Juras, V.,
Experiments with application of image reconstruction method based on perspective imaging techniques in X-ray CT mini system,
WSSIP08(33-36).
IEEE DOI 0806
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Chintalapani, G.[Gouthami], Jain, A.K.[Ameet K.], Burkhardt, D.H.[David H.], Prince, J.L.[Jerry L.], Fichtinger, G.[Gabor],
CTREC: C-arm tracking and reconstruction using elliptic curves,
MMBIA08(1-7).
IEEE DOI 0806
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van Velden, F.H.P., Kloet, R.W., van Berckel, B.N.M., Molthoff, C.F.M., Lammertsma, A.A., Boellaard, R.,
Gap Filling Strategies for 3-D-FBP Reconstructions of High-Resolution Research Tomograph Scans,
MedImg(27), No. 7, July 2008, pp. 934-942.
IEEE DOI 0808
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Petra, S.[Stefania], Schröder, A.[Andreas], Wieneke, B.[Bernhard], Schnörr, C.[Christoph],
On Sparsity Maximization in Tomographic Particle Image Reconstruction,
DAGM08(xx-yy).
Springer DOI 0806
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Morris, N.J.W.[Nigel J. W.], Kutulakos, K.N.[Kiriakos N.],
Reconstructing the Surface of Inhomogeneous Transparent Scenes by Scatter-Trace Photography,
ICCV07(1-8).
IEEE DOI 0710
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Jovanovic, I.[Ivana], Sbaiz, L.[Luciano], Vetterli, M.[Martin],
Tomographic Approach for Parametric Estimation of Local Diffusive Sources and Application to Heat Diffusion,
ICIP07(IV: 153-156).
IEEE DOI 0709
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Holt, K.M.[Kevin M.],
Geometric Calibration of Third-Generation Computed Tomography Scanners from Scans of Unknown Objects using Complementary Rays,
ICIP07(IV: 129-132).
IEEE DOI 0709
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Yin, X.X.[Xiao-Xia], Ng, B.W.H.[Brian W.H.], Ferguson, B.[Bradley], Abbott, D.[Derek],
Wavelet Based Local Coherent Tomography with an Application in Terahertz Imaging,
CAIP07(878-885).
Springer DOI 0708
BibRef

Ahmad, M.[Munir], Todd-Pokropek, A.[Andrew],
Non-uniform Resolution Recovery Using Median Priors in Tomographic Image Reconstruction Methods,
CAIP07(270-277).
Springer DOI 0708
BibRef

Chen, X.H.[Xiao-Han], Schmid, N.A.,
A Joint Shape-Intensity Estimation in Computerized Tomography in the Presence of High-Density Objects,
ICIP06(901-904).
IEEE DOI 0610
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Gerard, Y.[Yan],
Additive Subsets,
IWCIA06(347-353).
Springer DOI 0606
Analysis of tomography. BibRef

Kim, J.Y.,
Comparison of the Image Distortion Correction Methods for an X-Ray Digital Tomosynthesis System,
ICIAR05(286-293).
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Hashimoto, M., Matsuo, K., Koike, A., Hayashi, H., Shimono, T.,
CT image compression with level of interest,
ICIP04(V: 3185-3188).
IEEE DOI 0505
BibRef

Dulio, P.[Paolo], Frosini, A.[Andrea], Pagani, S.M.C.[Silvia M. C.],
Geometrical Characterization of the Uniqueness Regions Under Special Sets of Three Directions in Discrete Tomography,
DGCI16(105-116).
WWW Link. 1606
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Earlier:
Uniqueness Regions under Sets of Generic Projections in Discrete Tomography,
DGCI14(285-296).
Springer DOI 1410
BibRef

Barcucci, E.[Elena], Brocchi, S.[Stefano], Frosini, A.[Andrea],
Solving the Two Color Problem: An Heuristic Algorithm,
IWCIA11(298-310).
Springer DOI 1105
BibRef

Brocchi, S., Frosini, A., Rinaldi, S.,
Solving Some Instances of the 2-Color Problem,
DGCI09(505-516).
Springer DOI 0909
BibRef
And:
The 1-Color Problem and the Brylawski Model,
DGCI09(530-538).
Springer DOI 0909
BibRef

Frosini, A., Picouleau, C., Rinaldi, S.,
Reconstructing Binary Matrices with Neighborhood Constraints: An NP-hard Problem,
DGCI08(xx-yy).
Springer DOI 0804
BibRef

Frosini, A.[Andrea], Nivat, M.[Maurice],
Binary Matrices Under the Microscope: A Tomographical Problem,
IWCIA04(1-22).
Springer DOI 0505
BibRef

Weber, S.[Stefan], Schüle, T.[Thomas], Kuba, A.[Attila], Schnörr, C.[Christoph],
Binary Tomography with Deblurring,
IWCIA06(375-388).
Springer DOI 0606
BibRef

Kostler, H., Prummer, M., Rude, U., Hornegger, J.,
Adaptive variational sinogram interpolation of sparsely sampled CT data,
ICPR06(III: 778-781).
IEEE DOI 0609
BibRef

Numada, M., Nomura, T., Kamiya, K., Koshimizu, H., Tashiro, H.,
Sharpening of CT images by cubic interpolation using B-spline,
ICPR04(IV: 701-704).
IEEE DOI 0409
BibRef

Alvino, C.V.[Christopher V.], Yezzi, Jr., A.J.[Anthony J.],
Tomographic reconstruction of piecewise smooth images,
CVPR04(I: 576-581).
IEEE DOI 0408
BibRef

Temkin, J.M., Schmiederer, J.,
A hybrid hardware accelerated approach for tomographic reconstruction,
ICIP02(II: 637-640).
IEEE DOI 0210
BibRef

Kamalabadi, F.,
High-throughput Hyperspectral Imaging with Tomographic Reconstruction for Weak Signal Sources,
ICIP01(I: 309-312).
IEEE DOI 0108
BibRef

Ohta, J., Ogawa, K.,
Accurate Image Reconstruction with the Source Space Tree Algorithm (SSTA) for Compton CT,
ICIP01(I: 698-701).
IEEE DOI 0108
BibRef

Strahlen, K.,
Local Vector Tomography by Use of Wavelets,
ICIP00(Vol II: 617-620).
IEEE DOI 0008
BibRef

Osman, N.F., and Prince, J.L.,
Reconstruction of Vector Fields in Bounded Domain Vector Tomography,
ICIP97(I: 476-479).
IEEE DOI BibRef 9700

Bonifazzi, C., Maino, G., Tartari, A.,
A regularization method for unfolding the measured data of different X-ray spectrometers in Compton scattering tomography,
CIAP97(II: 436-444).
Springer DOI 9709
BibRef

Noumeir, R., Mailloux, G.E., Lemieux, R.,
Use of an optical flow algorithm to quantify and correct patient motion during tomographic acquisition,
ICIP96(III: 559-562).
IEEE DOI 9610
BibRef

Dusaussoy, N.J., Cao, Q.Z.[Qi-Zhi], Yancey, R.N., Stanley, J.H.,
Image processing for CT-assisted reverse engineering and part characterization,
ICIP95(III: 33-36).
IEEE DOI 9510
BibRef

Hanson, K.M., Cunningham, G.S., Jennings, Jr., G.R., Wolf, D.R.,
Tomographic reconstruction based on flexible geometric models,
ICIP94(II: 145-147).
IEEE DOI 9411
BibRef

Srinivas, C., Costa, M.H.M.,
Motion-compensated CT image reconstruction,
ICIP94(II: 849-853).
IEEE DOI 9411
BibRef

Yan, Z.Z., Eiho, S., Tanaka, H.,
Anatomical-map system for CT interpretation,
ICPR92(II:246-250).
IEEE DOI 9208
BibRef

Dinten, J.M.,
Tomographic reconstruction of axially symmetric objects: Regularization by a Markovian modelization,
ICPR90(II: 153-158).
IEEE DOI 9208
BibRef

Stark, H., Peng, H.[Hui],
Shape estimation in computer tomography from minimal data,
ICPR88(I: 184-186).
IEEE DOI 8811
BibRef

Huang, S.M., Dyakowski, T., Xie, C.G., Plaskowski, A.B., Xu, L.A., Beck, M.S.,
A tomographic flow imaging system based on capacitance measuring techniques,
ICPR88(I: 570-572).
IEEE DOI 8811
BibRef

Oswald, H.,
Three Dimensional Imaging from Computed Tomograms,
ISPDSA83(710-724). BibRef 8300

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Backprojection in Tomographic Image Reconstruction .


Last update:Mar 16, 2024 at 20:36:19