20.11.1 Magnetic Resonance Imaging Systems, Hardware Implementations

Ramos-Llordén, G., den Dekker, A.J., Sijbers, J.,
Partial Discreteness: A Novel Prior for Magnetic Resonance Image Reconstruction,
MedImg(36), No. 5, May 2017, pp. 1041-1053.
IEEE DOI 1609
Bayes methods, Gaussian mixture model, Image reconstruction, Magnetic resonance imaging, Probability density function, Reconstruction algorithms, Gaussian Mixture Model, MRI reconstruction, partial discreteness, segmentation, sparsity BibRef

Jia, Y., Gholipour, A., He, Z., Warfield, S.K.,
A New Sparse Representation Framework for Reconstruction of an Isotropic High Spatial Resolution MR Volume From Orthogonal Anisotropic Resolution Scans,
MedImg(36), No. 5, May 2017, pp. 1182-1193.
IEEE DOI 1705
Magnetic resonance imaging (MRI), orthogonal scans, overcomplete dictionary, partial volume effects (PVEs), sparse representation, super-resolution (SR), wavelet, fusion BibRef

Saucedo, A., Lefkimmiatis, S., Rangwala, N., Sung, K.,
Improved Computational Efficiency of Locally Low Rank MRI Reconstruction Using Iterative Random Patch Adjustments,
MedImg(36), No. 6, June 2017, pp. 1209-1220.
IEEE DOI 1706
Acceleration, Image reconstruction, Magnetic resonance imaging, Optimization, Partitioning algorithms, Transforms, Compressive sensing, locally low-rank regularization, parallel imaging, parameter, mapping BibRef

Liu, S.J.[Shu-Jun], Cao, J.X.[Jian-Xin], Liu, H.[Hongqing], Shen, X.D.[Xiao-Dong], Zhang, K.[Kui], Wang, P.[Pin],
MRI reconstruction using a joint constraint in patch-based total variational framework,
JVCIR(46), No. 1, 2017, pp. 150-164.
Elsevier DOI 1706
CS-MRI BibRef

Arduino, A., Zilberti, L., Chiampi, M., Bottauscio, O.,
CSI-EPT in Presence of RF-Shield for MR-Coils,
MedImg(36), No. 7, July 2017, pp. 1396-1404.
IEEE DOI 1707
Magnetic domains, Magnetic properties, Magnetic resonance imaging, Mathematical model, Minimization, Numerical models, Radio frequency, Contrast source inversion, Maxwell equations, electric properties tomography, finite element method, magnetic resonance imaging, specific, absorption, rate BibRef

Sakhaee, E., Entezari, A.,
Joint Inverse Problems for Signal Reconstruction via Dictionary Splitting,
SPLetters(24), No. 8, August 2017, pp. 1203-1207.
IEEE DOI 1708
discrete wavelet transforms, inverse problems, signal reconstruction, signal representation, Bregman splitting, DWT, SWT, dictionary splitting approach, discrete wavelet transform, joint inverse problems, orthogonal dictionaries, parallel sparse recovery problems, pseudoGibbs artifacts, redundant shift-invariant wavelet transform, signal reconstruction, sparse signal recovery, sparse signal representation, Discrete wavelet transforms, Image reconstruction, Noise reduction, Redundancy, Signal to noise ratio, Spinning, Compressed sensing, MRI, cycle spinning, dictionary splitting, shift-invariant wavelet transform, sparse, reconstruction BibRef

Selvi, G.U.V.[G. Uma Vetri], Nadarajan, R.,
CT and MRI image compression using wavelet-based contourlet transform and binary array technique,
RealTimeIP(13), No. 2, June 2017, pp. 261-272.
WWW Link. 1708
BibRef

Honarvar, M., Sahebjavaher, R.S., Rohling, R., Salcudean, S.E.,
A Comparison of Finite Element-Based Inversion Algorithms, Local Frequency Estimation, and Direct Inversion Approach Used in MRE,
MedImg(36), No. 8, August 2017, pp. 1686-1698.
IEEE DOI 1708
Elasticity, Elastography, Filter banks, Finite element analysis, Frequency estimation, Inverse problems, Mathematical model, Dynamic elastography, finite element method, inverse problem, magnetic resonance elastography, medical imaging, sparsity, regularization BibRef

Chaabene, S., Chaari, L.,
Bayesian myopic parallel MRI reconstruction,
ISIVC16(103-108)
IEEE DOI 1704
Bayes methods BibRef

Ulas, C.[Cagdas], Gómez, P.A.[Pedro A.], Krahmer, F.[Felix], Sperl, J.I.[Jonathan I.], Menzel, M.I.[Marion I.], Menze, B.H.[Bjoern H.],
Robust Reconstruction of Accelerated Perfusion MRI Using Local and Nonlocal Constraints,
RAMBO16(37-47).
Springer DOI 1703
BibRef

Bones, P., King, L., Millane, R.,
MR imaging near metal: The POP algorithm,
ICVNZ16(1-6)
IEEE DOI 1701
Fats BibRef

Zhu, K., Zhang, C., Zhang, J.,
Coherence Analysis of Compressive Sensing Based Magnetic Resonance Imaging Reconstruction,
DICTA16(1-7)
IEEE DOI 1701
Coherence BibRef

Chandra, S.S., Archchige, R., Ruben, G., Jin, J., Li, M., Kingston, A.M., Svalbe, I., Crozier, S.,
Finite Radial Reconstruction for Magnetic Resonance Imaging: A Theoretical Study,
DICTA16(1-6)
IEEE DOI 1701
Discrete Fourier transforms BibRef

Jin, K.H., Lee, D., Lee, J., Ye, J.C.,
Recent progresses of accelerated MRI using annihilating filter-based low-rank interpolation,
ICIP16(968-972)
IEEE DOI 1610
Acceleration BibRef

Zhao, Q., Meng, D., Kong, X., Xie, Q., Cao, W., Wang, Y., Xu, Z.,
A Novel Sparsity Measure for Tensor Recovery,
ICCV15(271-279)
IEEE DOI 1602
Brain modeling BibRef

Cardona, H.D.V.[Hernán Darío Vargas], Álvarez, M.A.[Mauricio A.], Orozco, Á.A.[Álvaro A.],
Generalized Wishart Processes for Interpolation Over Diffusion Tensor Fields,
ISVC15(II: 499-508).
Springer DOI 1601
BibRef

Rich, A.[Adam], Potter, L.C.[Lee C.], Ashi, J.N.[Joshua N.], Ahmad, R.[Rizwan],
Factor graphs for inverse problems: Accelerated phase contrast magnetic resonance imaging,
ICIP15(1026-1030)
IEEE DOI 1512
BibRef

Portejoie, P.[Pierre], Mure, S.[Simon], Benoit-Cattin, H.[Hugues], Grenier, T.[Thomas],
Locally controlled regularized spatiotemporal anisotropic diffusion,
ICIP15(4823-4827)
IEEE DOI 1512
Anisotropic Diffusion; Image Sequence Filtering; MRI; Regularization BibRef

Omer, O.A.[Osama A.], Bassiouny, M.A.[M. Atef], Morooka, K.[Ken'ichi],
Efficient Resolution Enhancement Algorithm for Compressive Sensing Magnetic Resonance Image Reconstruction,
CIAP15(I:519-527).
Springer DOI 1511
BibRef

Tarquino, J.[Jonathan], Rueda, A.[Andrea], Romero, E.[Eduardo],
Shearlet-based sparse representation for super-resolution in diffusion weighted imaging (DWI),
ICIP14(3897-3900)
IEEE DOI 1502
Dictionaries BibRef

Sun, H.[Hao], Grissom, W.A.[William A.], Fessler, J.A.[Jeffrey A.],
Regularized estimation of Bloch-Siegert B1-maps in MRI,
ICIP14(3646-3650)
IEEE DOI 1502
Algorithm design and analysis BibRef

Muckley, M.J.[Matthew J.], Fessler, J.A.[Jeffrey A.],
Fast MR image reconstruction with orthogonal wavelet regularization via shift-variant shrinkage,
ICIP14(3651-3655)
IEEE DOI 1502
Convergence BibRef

Zhang, M.Q.[Mei-Qing], Nie, H.[Huirao], Pei, Y.[Yang], Tao, L.M.[Lin-Mi],
Volume Reconstruction for MRI,
ICPR14(3351-3356)
IEEE DOI 1412
Dictionaries BibRef

Izydorczyk, G.[Grzegorz], Klepaczko, A.[Artur],
Computer Simulation of the SWI Protocol in Nuclear Magnetic Resonance Imaging,
ICCVG14(294-301).
Springer DOI 1410
BibRef

Uma, K., Chandrasekharan, K., Paul, J.S.,
Partial Fourier reconstruction using subspace projection,
NCVPRIPG13(1-4)
IEEE DOI 1408
biomedical MRI BibRef

Hyder, M.M.[Md Mashud], Mahata, K.[Kaushik],
Sparse sequence recovery via a maximum a posteriori estimation,
ICIP13(489-493)
IEEE DOI 1402
Compressed sensing BibRef

Rodrigues, M.L.[Miguel L.], Figueiredo, P.[Patrícia], Sanches, J.M.[João Miguel],
A Bayesian Approach to Perfusion Imaging Using ASL MRI,
IbPRIA13(691-698).
Springer DOI 1307
BibRef

Garcia-Gomez, J.M.[Juan M.], Robles, M.[Montserrat], van Huffel, S.[Sabine], Juan-Císcar, A.[Alfons],
Modelling of Magnetic Resonance Spectra Using Mixtures for Binned and Truncated Data,
IbPRIA07(II: 266-273).
Springer DOI 0706
BibRef

Garnaoui, H.H., Tewfik, A.H.,
Visual masking and the design of magnetic resonance image acquisition,
ICIP95(I: 625-628).
IEEE DOI 9510
BibRef

Kadah, Y.M., Tewfik, A.H.,
Theory of true-velocity duplex imaging using a single transducer,
ICIP95(I: 629-632).
IEEE DOI 9510
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Segmentation, Features, Models from Magnetic Resonance Data, MRI .

Last update:Sep 18, 2017 at 11:34:11