Hydrodynamic and Radiographic Toolbox (HART)
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Erik Skau | Brendt Wohlberg | Barry J. Warthen | Yoram Bresler | Michael T. McCann | Balasubramanya T. Nadiga | Michelle A. Espy | Anish Lahiri | Martin E. Schulze | Berk Iskender | Trevor Wilcox | Gary Salazar | Marc Louis Klasky | Jennifer Disterhaupt | Elena Guardincerri | J. Carroll | Luke Pfister | Luke Hovey | Albert Mendez | J. E. Coleman | Chris Randall Rose Rose | Yoseob Han | Theodore Mockler | Aimee Hungerford | Saiprad Ravishankar | Charlie Bouman | B. Wohlberg | Y. Bresler | C. Bouman | Yoseob Han | M. Espy | E. Guardincerri | B. Nadiga | T. Wilcox | E. Skau | M. Klasky | M. Schulze | L. Pfister | A. Hungerford | J. Coleman | B. Warthen | C. Rose | Jennifer Disterhaupt | J. Carroll | Luke Hovey | Gary Salazar | A. Mendez | T. Mockler | S. Ravishankar | Berk Iskender | Anish Lahiri | G. Salazar
[1] Jeffrey A. Fessler,et al. Optimization Methods for Magnetic Resonance Image Reconstruction: Key Models and Optimization Algorithms , 2020, IEEE Signal Processing Magazine.
[2] Jian Fu,et al. A deep learning reconstruction framework for X-ray computed tomography with incomplete data , 2019, PloS one.
[3] M. Klasky. A Correct Flat Field Model For DARHT , 2019 .
[4] Daniel Livescu,et al. Leveraging Bayesian analysis to improve accuracy of approximate models , 2019, J. Comput. Phys..
[5] Kees Joost Batenburg,et al. A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning , 2019, ArXiv.
[6] José M. Bioucas-Dias,et al. Image Restoration and Reconstruction using Targeted Plug-and-Play Priors , 2019, IEEE Transactions on Computational Imaging.
[7] Jeffrey A. Fessler,et al. Convolutional Analysis Operator Learning: Dependence on Training Data , 2019, IEEE Signal Processing Letters.
[8] Rebecca Willett,et al. Neumann Networks for Inverse Problems in Imaging , 2019, ArXiv.
[9] Brendt Wohlberg,et al. An Online Plug-and-Play Algorithm for Regularized Image Reconstruction , 2018, IEEE Transactions on Computational Imaging.
[10] Yoram Bresler,et al. Learning Filter Bank Sparsifying Transforms , 2018, IEEE Transactions on Signal Processing.
[11] Jeffrey A. Fessler,et al. Adaptive Restart of the Optimized Gradient Method for Convex Optimization , 2017, J. Optim. Theory Appl..
[12] Xiaoqiang Luo,et al. An Image Reconstruction Method Based on Total Variation and Wavelet Tight Frame for Limited-Angle CT , 2018, IEEE Access.
[13] Daniël M Pelt,et al. A mixed-scale dense convolutional neural network for image analysis , 2017, Proceedings of the National Academy of Sciences.
[14] Heye Zhang,et al. Reweighted Anisotropic Total Variation Minimization for Limited-Angle CT Reconstruction , 2017, IEEE Transactions on Nuclear Science.
[15] Dong Liang,et al. An improved statistical iterative algorithm for sparse-view and limited-angle CT image reconstruction , 2017, Scientific Reports.
[16] Jong Chul Ye,et al. Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction , 2017, ArXiv.
[17] Michael Unser,et al. Deep Convolutional Neural Network for Inverse Problems in Imaging , 2016, IEEE Transactions on Image Processing.
[18] Lei Zhang,et al. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising , 2016, IEEE Transactions on Image Processing.
[19] Jong Chul Ye,et al. Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis , 2016, ArXiv.
[20] Andreas K. Maier,et al. Deep Learning Computed Tomography , 2016, MICCAI.
[21] Jiayu Zhou,et al. Asynchronous Multi-task Learning , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).
[22] David M. Blei,et al. Variational Inference: A Review for Statisticians , 2016, ArXiv.
[23] Ming Yan,et al. ARock: an Algorithmic Framework for Asynchronous Parallel Coordinate Updates , 2015, SIAM J. Sci. Comput..
[24] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[25] Igor Mezic,et al. On applications of the spectral theory of the Koopman operator in dynamical systems and control theory , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).
[26] Clarence W. Rowley,et al. A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition , 2014, Journal of Nonlinear Science.
[27] Steven L. Brunton,et al. On dynamic mode decomposition: Theory and applications , 2013, 1312.0041.
[28] Brendt Wohlberg,et al. Plug-and-Play priors for model based reconstruction , 2013, 2013 IEEE Global Conference on Signal and Information Processing.
[29] Laurent Hascoët,et al. The Tapenade automatic differentiation tool: Principles, model, and specification , 2013, TOMS.
[30] Klaus Diepold,et al. Analysis Operator Learning and its Application to Image Reconstruction , 2012, IEEE Transactions on Image Processing.
[31] Aleksandra Pizurica,et al. Iterative CT Reconstruction Using Shearlet-Based Regularization , 2012, IEEE Transactions on Nuclear Science.
[32] Lei Zhang,et al. Low-Dose X-ray CT Reconstruction via Dictionary Learning , 2012, IEEE Transactions on Medical Imaging.
[33] H. Makaruk. Generalization of inverse Abel transform 3D objects reconstruction from single radiographs for selected cases not fulfilling the axial symmetry assumption , 2012 .
[34] Stephen P. Boyd,et al. An ADMM Algorithm for a Class of Total Variation Regularized Estimation Problems , 2012, 1203.1828.
[35] Daniel J. Tward,et al. Series of 4D adult XCAT phantoms for imaging research and dosimetry , 2012, Medical Imaging.
[36] Hiêp Quang Luong,et al. Augmented Lagrangian based reconstruction of non-uniformly sub-Nyquist sampled MRI data , 2011, Signal Process..
[37] Rémi Gribonval,et al. Analysis operator learning for overcomplete cosparse representations , 2011, 2011 19th European Signal Processing Conference.
[38] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[39] Yoram Bresler,et al. MR Image Reconstruction From Highly Undersampled k-Space Data by Dictionary Learning , 2011, IEEE Transactions on Medical Imaging.
[40] H. Makaruk. 3D perturbation of the inverse Abel transform , 2011 .
[41] Pascal Frossard,et al. Dictionary Learning , 2011, IEEE Signal Processing Magazine.
[42] Kathleen M. Carley,et al. AutoMap User's Guide 2011 , 2011 .
[43] J. M. Sanz-Serna,et al. Optimal tuning of the hybrid Monte Carlo algorithm , 2010, 1001.4460.
[44] P. Schmid,et al. Dynamic mode decomposition of numerical and experimental data , 2008, Journal of Fluid Mechanics.
[45] I. Mezić,et al. Spectral analysis of nonlinear flows , 2009, Journal of Fluid Mechanics.
[46] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[47] E. Sidky,et al. Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization , 2008, Physics in medicine and biology.
[48] Robert Cierniak,et al. A New Approach to Image Reconstruction from Projections Using a Recurrent Neural Network , 2008, Int. J. Appl. Math. Comput. Sci..
[49] Thierry Blu,et al. SURE-LET Multichannel Image Denoising: Interscale Orthonormal Wavelet Thresholding , 2008, IEEE Transactions on Image Processing.
[50] Jie Tang,et al. Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets. , 2008, Medical physics.
[51] Stéphane Mallat,et al. A Wavelet Tour of Signal Processing - The Sparse Way, 3rd Edition , 2008 .
[52] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[53] Viktor K. Decyk,et al. UPIC: A framework for massively parallel particle-in-cell codes , 2007, Comput. Phys. Commun..
[54] Kathleen M. Carley,et al. AutoMap User's Guide , 2006 .
[55] Laurent Demanet,et al. Fast Discrete Curvelet Transforms , 2006, Multiscale Model. Simul..
[56] Jean-Michel Morel,et al. A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[57] E. Candès,et al. New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities , 2004 .
[58] Kannan Ramchandran,et al. Wavelet denoising by recursive cycle spinning , 2002, Proceedings. International Conference on Image Processing.
[59] G. Caporaso,et al. Status of the dual axis radiographic hydrodynamics test (DARHT) facility , 2002, 2002 14th International Conference on High-Power Particle Beams (BEAMS).
[60] D. Rovang,et al. Coupled particle-in-cell and Monte Carlo transport modeling of intense radiographic sources , 2002 .
[61] J. Fessler,et al. Spatial resolution properties of penalized-likelihood image reconstruction: space-invariant tomographs , 1996, 5th IEEE EMBS International Summer School on Biomedical Imaging, 2002..
[62] Kenneth M. Hanson,et al. Operation of the Bayes Inference Engine , 1999 .
[63] Christian H. Bischof,et al. ADIC: an extensible automatic differentiation tool for ANSI‐C , 1997, Softw. Pract. Exp..
[64] Klaus Mueller,et al. The weighted-distance scheme: a globally optimizing projection ordering method for ART , 1997, IEEE Transactions on Medical Imaging.
[65] Kenneth M. Hanson,et al. THE BAYES INFERENCE ENGINE , 1996 .
[66] Jorge Nocedal,et al. A Limited Memory Algorithm for Bound Constrained Optimization , 1995, SIAM J. Sci. Comput..
[67] D. L. Book,et al. The Sedov self-similar point blast solutions in nonuniform media , 1994 .
[68] David W. Juedes,et al. A taxonomy of automatic differentiation tools , 1991 .
[69] J. M. McGlaun,et al. CTH: A three-dimensional shock wave physics code , 1990 .
[70] M. Bertero. Linear Inverse and III-Posed Problems , 1989 .
[71] R. Fletcher. Practical Methods of Optimization , 1988 .
[72] L. Shepp,et al. A Statistical Model for Positron Emission Tomography , 1985 .
[73] L. Feldkamp,et al. Practical cone-beam algorithm , 1984 .
[74] A. Kak,et al. Simultaneous Algebraic Reconstruction Technique (SART): A Superior Implementation of the Art Algorithm , 1984, Ultrasonic imaging.
[75] Y. Nesterov. A method for unconstrained convex minimization problem with the rate of convergence o(1/k^2) , 1983 .
[76] David S. Kershaw,et al. LASNEX code for inertial confinement fusion , 1977 .
[77] B. F. Logan,et al. The Fourier reconstruction of a head section , 1974 .
[78] Martin J. Berger,et al. Penetration and Diffusion of X Rays , 1959 .
[79] B. O. Koopman,et al. Hamiltonian Systems and Transformation in Hilbert Space. , 1931, Proceedings of the National Academy of Sciences of the United States of America.