Liang, Z.P.[Zhi-Pei],
Lauterbur, P.C.,
A generalized series approach to MR spectroscopic imaging,
MedImg(10), No. 2, June 1991, pp. 132-137.
IEEE Top Reference. This is the work that led to the 2003 Nobel Prize for Lauterbur.
BibRef
9106
Liang, Z.P.[Zhi-Pei],
Lauterbur, P.C.,
An efficient method for dynamic magnetic resonance imaging,
MedImg(13), No. 4, December 1994, pp. 677-686.
IEEE Top Reference.
BibRef
9412
Sebastiani, G.,
Godtliebsen, F.,
Jones, R.A.,
Haraldseth, O.,
Muller, T.B.,
Rinck, P.A.,
Analysis of dynamic magnetic resonance images,
MedImg(15), No. 3, June 1996, pp. 268-277.
IEEE Top Reference.
0203
BibRef
And:
Correction:
MedImg(16), No. 1, February 1997, pp. 123-124.
IEEE Top Reference.
0205
BibRef
Petersson, J.S.,
Christoffersson, J.O.,
Multidimensional k-space model for analysis of flow-related phenomena
in MR imaging,
IJIST(10), No. 2, 1999, pp. 115-127.
BibRef
9900
Kerwin, W.S.,
Prince, J.L.,
Tracking MR tag surfaces using a spatiotemporal filter and interpolator,
IJIST(10), No. 2, 1999, pp. 128-142.
BibRef
9900
Earlier:
MR tag surface tracking using a spatio-temporal filter/interpolator,
ICIP98(I: 699-703).
IEEE DOI
9810
BibRef
Yang, W.F.[Wei-Fang],
Smith, M.R.,
Using an MRI distortion transfer function to characterize the ghosts in
motion-corrupted images,
MedImg(19), No. 6, June 2000, pp. 577-584.
IEEE Top Reference.
0110
BibRef
van de Walle, R.,
Barrett, H.H.,
Myers, K.J.,
Aitbach, M.I.,
Desplanques, B.,
Gmitro, A.F.,
Cornelis, J.,
Lemahieu, I.,
Reconstruction of MR images from data acquired on a general nonregular
grid by pseudoinverse calculation,
MedImg(19), No. 12, December 2000, pp. 1160-1167.
IEEE Top Reference.
0110
BibRef
van de Walle, R.,
Desplanques, B.,
Lemahieu, I.,
Continuous pseudo-inverse image reconstruction in spiral magnetic
resonance imaging,
CIAP99(762-767).
IEEE DOI
9909
BibRef
van de Walle, R.[Rik],
Lemahieu, I.[Ignace],
Achten, E.[Eric],
Two motion-detection algorithms for projection-reconstruction magnetic
resonance imaging: Theory and experimental verification,
CIAP97(II: 688-696).
Springer DOI
9709
BibRef
Panych, L.P.[Lawrence P.],
Zientara, G.P.[Gary P.],
Jolesz, F.A.[Ferenc A.],
MR image encoding by spatially selective RF excitation:
An analysis using linear response models,
IJIST(10), No. 2, 1999, pp. 143-150.
BibRef
9900
Zientara, G.P.[Gary P.],
Panych, L.P.[Lawrence P.],
Jolesz, F.A.[Ferenc A.],
Near-optimal spatial encoding for dynamically adaptive MRI:
Mathematical principles and computational methods,
IJIST(10), No. 2, 1999, pp. 151-165.
BibRef
9900
Hoge, W.S.,
Miller, E.L.,
Lev-Ari, H.,
Brooks, D.H.,
Karl, W.C.,
Panych, L.P.,
An efficient region of interest acquisition method for
dynamic magnetic resonance imaging,
IP(10), No. 7, July 2001, pp. 1118-1128.
IEEE DOI
0108
BibRef
Panych, L.P.,
Theoretical comparison of Fourier and wavelet encoding in magnetic
resonance imaging,
MedImg(15), No. 2, April 1996, pp. 141-153.
IEEE Top Reference.
0203
BibRef
Hoge, W.S.,
Miller, E.L.,
Lev-Ari, H.,
Brooks, D.H.,
Panych, L.P.,
A doubly adaptive approach to dynamic MRI sequence estimation,
IP(11), No. 10, October 2002, pp. 1168-1178.
IEEE DOI
0211
BibRef
Hoge, W.S.,
A subspace identification extension to the phase correlation method,
MedImg(22), No. 2, February 2003, pp. 277-280.
IEEE Top Reference.
0304
BibRef
Ozturk, C.,
Derbyshire, J.A.,
McVeigh, E.R.M.,
Estimating motion from MRI data,
PIEEE(91), No. 10, October 2003, pp. 1627-1648.
IEEE DOI
0310
BibRef
Ulloa, J.L.,
Guarini, M.,
Guesalaga, A.,
Irarrazaval, P.,
Chebyshev Series for Designing RF Pulses Employing an Optimal Control
Approach,
MedImg(23), No. 11, November 2004, pp. 1445-1452.
IEEE Abstract.
0411
MRI images.
BibRef
Irarrazaval, P.[Pablo],
Sampling Less and Reconstructing More for Magnetic Resonance Imaging,
PSIVT07(3).
Springer DOI
0712
BibRef
Prieto, C.[Claudia],
Guarini, M.[Marcelo],
Hajnal, J.[Joseph],
Irarrazaval, P.[Pablo],
Motion Estimation Applied to Reconstruct Undersampled Dynamic MRI,
PSIVT07(522-532).
Springer DOI
0712
BibRef
Twellmann, T.,
Lichte, O.,
Nattkemper, T.W.,
An Adaptive Tissue Characterization Network for Model-Free
Visualization of Dynamic Contrast-Enhanced Magnetic Resonance Image
Data,
MedImg(24), No. 10, October 2005, pp. 1256-1266.
IEEE DOI
0510
BibRef
Landi, G.,
Piccolomini, E.L.[E. Loli],
Representation of High Resolution Images from Low Sampled Fourier Data:
Applications to Dynamic MRI,
JMIV(26), No. 1-2, November 2006, pp. 27-40.
Springer DOI
0701
BibRef
Shin, T.,
Nielsen, J.F.,
Nayak, K.S.,
Accelerating Dynamic Spiral MRI by Algebraic Reconstruction From
Undersampled t Space,
MedImg(26), No. 7, July 2007, pp. 917-924.
IEEE DOI
0707
BibRef
Felfoul, O.,
Mathieu, J.B.,
Beaudoin, G.,
Martel, S.,
In Vivo MR-Tracking Based on Magnetic Signature Selective Excitation,
MedImg(27), No. 1, January 2008, pp. 28-35.
IEEE DOI
0712
BibRef
Sumbul, U.,
Santos, J.M.,
Pauly, J.M.,
Improved Time Series Reconstruction for Dynamic Magnetic Resonance
Imaging,
MedImg(28), No. 7, July 2009, pp. 1093-1104.
IEEE DOI
0906
BibRef
Sumbul, U.,
Santos, J.M.,
Pauly, J.M.,
A Practical Acceleration Algorithm for Real-Time Imaging,
MedImg(28), No. 12, December 2009, pp. 2042-2051.
IEEE DOI
0912
BibRef
Kelm, B.M.,
Menze, B.H.,
Nix, O.,
Zechmann, C.M.,
Hamprecht, F.A.,
Estimating Kinetic Parameter Maps From Dynamic Contrast-Enhanced MRI
Using Spatial Prior Knowledge,
MedImg(28), No. 10, October 2009, pp. 1534-1547.
IEEE DOI
0910
BibRef
Van, A.T.,
Karampinos, D.C.,
Georgiadis, J.G.,
Sutton, B.P.,
K-Space and Image-Space Combination for Motion-Induced Phase-Error
Correction in Self-Navigated Multicoil Multishot DWI,
MedImg(28), No. 11, November 2009, pp. 1770-1780.
IEEE DOI
0911
BibRef
Van, A.T.,
Hernando, D.,
Sutton, B.P.,
Motion-Induced Phase Error Estimation and Correction in 3D Diffusion
Tensor Imaging,
MedImg(30), No. 11, November 2011, pp. 1933-1940.
IEEE DOI
1111
BibRef
Elen, A.,
Hermans, J.,
Ganame, J.,
Loeckx, D.,
Bogaert, J.,
Maes, F.,
Suetens, P.,
Automatic 3-D Breath-Hold Related Motion Correction of Dynamic
Multislice MRI,
MedImg(29), No. 3, March 2010, pp. 868-878.
IEEE DOI
1003
BibRef
Jung, H.[Hong],
Ye, J.C.[Jong Chul],
Motion estimated and compensated compressed sensing dynamic magnetic
resonance imaging: What we can learn from video compression techniques,
IJIST(20), No. 2, June 2010, pp. 81-98.
DOI Link
1006
BibRef
Chen, L.,
Choyke, P.L.,
Chan, T.H.,
Chi, C.Y.,
Wang, G.,
Wang, Y.,
Tissue-Specific Compartmental Analysis for Dynamic Contrast-Enhanced MR
Imaging of Complex Tumors,
MedImg(30), No. 12, December 2011, pp. 2044-2058.
IEEE DOI
1112
BibRef
Lingala, S.G.,
Hu, Y.,
di Bella, E.V.R.[Edward V. R.],
Jacob, M.,
Accelerated Dynamic MRI Exploiting Sparsity and Low-Rank Structure:
k-t SLR,
MedImg(30), No. 5, May 2011, pp. 1042-1054.
IEEE DOI
1105
BibRef
Balachandrasekaran, A.,
Magnotta, V.,
Jacob, M.,
Recovery of Damped Exponentials Using Structured Low Rank Matrix
Completion,
MedImg(36), No. 10, October 2017, pp. 2087-2098.
IEEE DOI
1710
Approximation algorithms, Computational complexity, Convolution,
Discrete Fourier transforms, Indexes, Jacobian matrices,
Hankel/Toeplitz matrix,
parameter mapping, regularized recovery, smoothness
BibRef
Balachandrasekaran, A.,
Ongie, G.,
Jacob, M.,
Accelerated dynamic MRI using structured low rank matrix completion,
ICIP16(1858-1862)
IEEE DOI
1610
Acceleration
BibRef
Welsh, C.L.,
di Bella, E.V.R.,
Hsu, E.W.,
Higher-Order Motion-Compensation for In Vivo Cardiac Diffusion Tensor
Imaging in Rats,
MedImg(34), No. 9, September 2015, pp. 1843-1853.
IEEE DOI
1509
Acceleration
BibRef
Hu, Y.,
Lingala, S.G.,
Jacob, M.,
A Fast Majorize-Minimize Algorithm for the Recovery of Sparse and
Low-Rank Matrices,
IP(21), No. 2, February 2012, pp. 742-753.
IEEE DOI
1201
BibRef
Lingala, S.G.,
Jacob, M.,
Blind Compressive Sensing Dynamic MRI,
MedImg(32), No. 6, 2013, pp. 1132-1145.
IEEE DOI
1307
K-SVD; dynamic magnetic resonance imaging (DMRI)
BibRef
Hu, Y.[Yue],
Jacob, M.[Mathews],
Higher Degree Total Variation (HDTV) Regularization for Image Recovery,
IP(21), No. 5, May 2012, pp. 2559-2571.
IEEE DOI
1204
BibRef
Hu, Y.,
Lu, X.,
Jacob, M.,
Multiple degree total variation (MDTV) regularization for image
restoration,
ICIP16(1958-1962)
IEEE DOI
1610
HDTV
BibRef
Hu, Y.[Yue],
Lin, D.[Disi],
Zhao, K.S.[Kuang-Shi],
Accelerated 4D Mr Image Reconstruction Using Joint Higher Degree
Total Variation And Local Low-Rank Constraints,
ICIP20(2935-2939)
IEEE DOI
2011
Image reconstruction, Acceleration, Optimization,
Magnetic resonance imaging, TV,
3D higher degree total variation
BibRef
Hu, Y.[Yue],
Ongie, G.,
Ramani, S.,
Jacob, M.,
Generalized Higher Degree Total Variation (HDTV) Regularization,
IP(23), No. 6, June 2014, pp. 2423-2435.
IEEE DOI
1406
image processing
BibRef
Ongie, G.,
Jacob, M.,
Recovery of Discontinuous Signals Using Group Sparse Higher Degree
Total Variation,
SPLetters(22), No. 9, September 2015, pp. 1414-1418.
IEEE DOI
1503
Analytical models
BibRef
de Senneville, B.D.,
Ries, M.,
Maclair, G.,
Moonen, C.T.W.,
MR-Guided Thermotherapy of Abdominal Organs Using a Robust PCA-Based
Motion Descriptor,
MedImg(30), No. 11, November 2011, pp. 1987-1995.
IEEE DOI
1111
BibRef
de Senneville, B.D.[B. Denis],
Mougenot, C.,
Desbarats, P.,
Quesson, B.,
Moonen, C.T.W.,
On-Line Mobile Organ Tracking for Non-Invasive Local Hyperthermia,
ICIP06(2845-2848).
IEEE DOI
0610
BibRef
de Senneville, B.D.[B. Denis],
Desbarats, P.,
Quesson, B.,
Moonen, C.T.W.,
3D Motion Estimation for On-Line MR Temperature Mapping,
ICIP05(III: 101-104).
IEEE DOI
0512
BibRef
de Senneville, B.D.[B. Denis],
Quesson, B.,
Desbarats, P.,
Salomir, R.,
Palussiere, J.,
Moonen, C.T.W.,
Atlas-based motion correction for on-line MR temperature mapping,
ICIP04(IV: 2571-2574).
IEEE DOI
0505
BibRef
Song, T.[Ting],
Lee, V.S.[Vivian S.],
Chen, Q.[Qun],
Rusinek, H.[Henry],
Laine, A.F.[Andrew F.],
An automated three-dimensional plus time registration framework for
dynamic MR renography,
JVCIR(21), No. 1, January 2010, pp. 1-8.
Elsevier DOI
1002
MR renography; Dynamic MR; 3D plus time registration; Dynamic
contrast-enhanced imaging; Wavelet representation; Anisotropic
diffusion; Fourier-based registration; Automated respiratory motion
correction; WRFT
BibRef
Majumdar, A.[Angshul],
Ward, R.K.[Rabab K.],
Aboulnasr, T.,
Compressed Sensing Based Real-Time Dynamic MRI Reconstruction,
MedImg(31), No. 12, December 2012, pp. 2253-2266.
IEEE DOI
1212
BibRef
Majumdar, A.[Angshul],
Ward, R.K.[Rabab K.],
Learning space-time dictionaries for blind compressed sensing dynamic
MRI reconstruction,
ICIP15(4550-4554)
IEEE DOI
1512
Compressed Sensing
BibRef
Rahim, M.[Mehdi],
Bellemare, M.E.[Marc-Emmanuel],
Bulot, R.[Rémy],
Pirró, N.[Nicolas],
A Diffeomorphic Mapping Based Characterization of Temporal Sequences:
Application to the Pelvic Organ Dynamics Assessment,
JMIV(47), No. 1-2, September 2013, pp. 151-164.
Springer DOI
1307
BibRef
Earlier: A1, A2, A4, A3:
A Diffeomorphic Matching Based Characterization of the Pelvic Organ
Dynamics,
CAIP11(I: 469-476).
Springer DOI
1109
BibRef
Earlier: A1, A2, A3, A4:
Pelvic Organs Dynamic Feature Analysis for MRI Sequence Discrimination,
ICPR10(2496-2499).
IEEE DOI
1008
BibRef
Vaillant, G.,
Prieto, C.,
Kolbitsch, C.,
Penney, G.,
Schaeffter, T.,
Retrospective Rigid Motion Correction in k-Space for Segmented Radial
MRI,
MedImg(33), No. 1, January 2014, pp. 1-10.
IEEE DOI
1402
biomedical MRI
BibRef
Tremoulheac, B.,
Dikaios, N.,
Atkinson, D.,
Arridge, S.R.,
Dynamic MR Image Reconstruction: Separation From Undersampled
(k,t)-Space via Low-Rank Plus Sparse Prior,
MedImg(33), No. 8, August 2014, pp. 1689-1701.
IEEE DOI
1408
Image reconstruction
BibRef
Caballero, J.,
Price, A.N.,
Rueckert, D.,
Hajnal, J.V.,
Dictionary Learning and Time Sparsity for Dynamic MR Data
Reconstruction,
MedImg(33), No. 4, April 2014, pp. 979-994.
IEEE DOI
1404
Acceleration
BibRef
Bostan, E.,
Lefkimmiatis, S.,
Vardoulis, O.,
Stergiopulos, N.,
Unser, M.,
Improved Variational Denoising of Flow Fields with Application to
Phase-Contrast MRI Data,
SPLetters(22), No. 6, June 2015, pp. 762-766.
IEEE DOI
1411
Jacobian matrices
BibRef
Hutter, J.,
Schmitt, P.,
Saake, M.,
Stubinger, A.,
Grimm, R.,
Forman, C.,
Greiser, A.,
Hornegger, J.,
Maier, A.,
Multi-Dimensional Flow-Preserving Compressed Sensing (MuFloCoS) for
Time-Resolved Velocity-Encoded Phase Contrast MRI,
MedImg(34), No. 2, February 2015, pp. 400-414.
IEEE DOI
1502
Acceleration
BibRef
Lingala, S.G.,
DiBella, E.,
Jacob, M.,
Deformation Corrected Compressed Sensing (DC-CS):
A Novel Framework for Accelerated Dynamic MRI,
MedImg(34), No. 1, January 2015, pp. 72-85.
IEEE DOI
1502
Fourier analysis
BibRef
Lingala, S.G.[Sajan Goud],
Zhu, Y.H.[Ying-Hua],
Kim, Y.C.[Yoon-Chul],
Toutios, A.[Asterios],
Narayanan, S.[Shrikanth],
Nayak, K.[Krishna],
High-frame-rate real-time imaging of speech production,
SPIE(Newsroom), June 3, 2015.
DOI Link
1507
Sparse sampling and constrained reconstruction enable 83-frames/second
real-time magnetic resonance imaging, providing new insights into the
dynamics of vocal-tract shaping.
BibRef
Babayeva, M.,
Kober, T.,
Knowles, B.,
Herbst, M.,
Meuli, R.,
Zaitsev, M.,
Krueger, G.,
Accuracy and Precision of Head Motion Information in Multi-Channel
Free Induction Decay Navigators for Magnetic Resonance Imaging,
MedImg(34), No. 9, September 2015, pp. 1879-1889.
IEEE DOI
1509
Accuracy
BibRef
Poddar, S.,
Jacob, M.,
Dynamic MRI Using SmooThness Regularization on Manifolds (SToRM),
MedImg(35), No. 4, April 2016, pp. 1106-1115.
IEEE DOI
1604
biomedical MRI
BibRef
Hering, J.,
Wolf, I.,
Maier-Hein, K.H.,
Multi-Objective Memetic Search for Robust Motion and Distortion
Correction in Diffusion MRI,
MedImg(35), No. 10, October 2016, pp. 2280-2291.
IEEE DOI
1610
Head
BibRef
Roeloffs, V.[Volkert],
Wang, X.Q.[Xiao-Qing],
Sumpf, T.J.[Tilman J.],
Untenberger, M.[Markus],
Voit, D.[Dirk],
Frahm, J.[Jens],
Model-Based Reconstruction for T1 Mapping Using Single-Shot
Inversion-Recovery Radial FLASH,
IJIST(26), No. 4, 2016, pp. 254-263.
DOI Link
1701
T1 mapping
BibRef
Roeloffs, V.[Volkert],
Uecker, M.,
Frahm, J.,
Joint T1 and T2 Mapping With Tiny Dictionaries and
Subspace-Constrained Reconstruction,
MedImg(39), No. 4, April 2020, pp. 1008-1014.
IEEE DOI
2004
Dictionaries, Manifolds, Approximation error,
Magnetic resonance imaging, Image reconstruction,
quantitative MRI
BibRef
Ravishankar, S.[Saiprasad],
Moore, B.E.[Brian E.],
Nadakuditi, R.R.,
Fessler, J.A.,
Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly
Accelerated Dynamic Imaging,
MedImg(36), No. 5, May 2017, pp. 1116-1128.
IEEE DOI
1705
BibRef
Earlier:
LASSI: A low-rank and adaptive sparse signal model for highly
accelerated dynamic imaging,
IVMSP16(1-5)
IEEE DOI
1608
Adaptation models, Compressed sensing, Data models, Dictionaries,
Image reconstruction, Magnetic resonance imaging,
Dictionary learning, dynamic imaging, inverse problems,
machine learning, magnetic resonanace imaging,
nonconvex optimization, sparse representations, structured models.
BibRef
Moore, B.E.[Brian E.],
Ravishankar, S.[Saiprasad],
Online data-driven dynamic image restoration using DINO-KAT models,
ICIP17(3590-3594)
IEEE DOI
1803
DIctioNary with lOw-ranK AToms.
reconstructing images and videos from limited or corrupted measurements.
Denoising, inpainting.
Adaptation models, Atomic measurements, Dictionaries,
Image reconstruction, Sparse matrices, Spatiotemporal phenomena,
online algorithms
BibRef
Alansary, A.,
Rajchl, M.,
McDonagh, S.G.,
Murgasova, M.,
Damodaram, M.,
Lloyd, D.F.A.,
Davidson, A.,
Rutherford, M.,
Hajnal, J.V.,
Rueckert, D.,
Kainz, B.,
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction
of Fetal MRI,
MedImg(36), No. 10, October 2017, pp. 2031-2044.
IEEE DOI
1710
biological organs, biomedical MRI, blood vessels, data acquisition,
graphics processing units, image reconstruction,
image registration, image resolution, medical
motion compensation, obstetrics, pneumodynamics,
BibRef
Nakarmi, U.,
Wang, Y.,
Lyu, J.,
Liang, D.,
Ying, L.,
A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold
Recovery in Highly Accelerated Dynamic MRI,
MedImg(36), No. 11, November 2017, pp. 2297-2307.
IEEE DOI
1711
Magnetic resonance imaging, Manifolds,
Principal component analysis, Low rank models,
BibRef
Tirunagari, S.[Santosh],
Poh, N.[Norman],
Wells, K.[Kevin],
Bober, M.[Miroslaw],
Gorden, I.[Isky],
Windridge, D.[David],
Movement correction in DCE-MRI through windowed and reconstruction
dynamic mode decomposition,
MVA(28), No. 3-4, May 2017, pp. 393-407.
Springer DOI
1704
BibRef
Nirouei, M.[Mahyar],
Pouladian, M.[Majid],
Abdolmaleki, P.[Parviz],
Akhlaghpoor, S.[Shahram],
Curvelet analysis of breast masses on dynamic magnetic resonance
mammography,
IET-IPR(12), No. 5, May 2018, pp. 745-750.
DOI Link
1804
BibRef
Haskell, M.W.,
Cauley, S.F.,
Wald, L.L.,
TArgeted Motion Estimation and Reduction (TAMER): Data Consistency
Based Motion Mitigation for MRI Using a Reduced Model Joint
Optimization,
MedImg(37), No. 5, May 2018, pp. 1253-1265.
IEEE DOI
1805
Biomedical imaging, Computational modeling, Image reconstruction,
Navigation, Optimization, Motion correction, forward modeling,
model reduction
BibRef
Karani, N.,
Tanner, C.,
Kozerke, S.,
Konukoglu, E.,
Reducing Navigators in Free-Breathing Abdominal MRI via Temporal
Interpolation Using Convolutional Neural Networks,
MedImg(37), No. 10, October 2018, pp. 2333-2343.
IEEE DOI
1810
Navigation, Interpolation, Magnetic resonance imaging,
Image resolution,
temporal image interpolation
BibRef
Xiao, S.,
Deng, H.,
Duan, C.,
Xie, J.,
Li, H.,
Sun, X.,
Ye, C.,
Zhou, X.,
Highly and Adaptively Undersampling Pattern for Pulmonary
Hyperpolarized 129Xe Dynamic MRI,
MedImg(38), No. 5, May 2019, pp. 1240-1250.
IEEE DOI
1905
Magnetic resonance imaging, Lung, Image reconstruction,
Ventilation, Dynamics, Acceleration, Heuristic algorithms,
compressed sensing (CS)
BibRef
Senel, L.K.,
Kilic, T.,
Gungor, A.,
Kopanoglu, E.,
Guven, H.E.,
Saritas, E.U.,
Koc, A.,
Çukur, T.,
Statistically Segregated k-Space Sampling for Accelerating
Multiple-Acquisition MRI,
MedImg(38), No. 7, July 2019, pp. 1701-1714.
IEEE DOI
1907
Magnetic resonance imaging, Image reconstruction, Acceleration,
Probability density function, Aggregates, Correlation,
compressed sensing
BibRef
van Niekerk, A.,
Meintjes, E.,
van der Kouwe, A.,
A Wireless Radio Frequency Triggered Acquisition Device (WRAD) for
Self-Synchronised Measurements of the Rate of Change of the MRI
Gradient Vector Field for Motion Tracking,
MedImg(38), No. 7, July 2019, pp. 1610-1621.
IEEE DOI
1907
Magnetic resonance imaging, Magnetometers, Encoding,
Mathematical model, Voltage measurement, Wireless communication,
motion
BibRef
Scannell, C.M.,
Villa, A.D.M.,
Lee, J.,
Breeuwer, M.,
Chiribiri, A.,
Robust Non-Rigid Motion Compensation of Free-Breathing Myocardial
Perfusion MRI Data,
MedImg(38), No. 8, August 2019, pp. 1812-1820.
IEEE DOI
1908
Motion compensation, Myocardium, Magnetic resonance imaging,
Principal component analysis, Image registration, Strain, Dynamics,
tracer-kinetic modeling
BibRef
Christodoulou, A.G.,
Lingala, S.G.,
Accelerated Dynamic Magnetic Resonance Imaging Using Learned
Representations: A New Frontier in Biomedical Imaging,
SPMag(37), No. 1, January 2020, pp. 83-93.
IEEE DOI
2001
Magnetic resonance imaging, Compressed sensing,
Adaptation models, Data models, Matrix decomposition
BibRef
Liu, Y.P.[Yi-Peng],
Liu, T.T.[Teng-Teng],
Liu, J.[Jiani],
Zhu, C.[Ce],
Smooth robust tensor principal component analysis for compressed
sensing of dynamic MRI,
PR(102), 2020, pp. 107252.
Elsevier DOI
2003
Robust tensor principal component analysis,
Compressed sensing, Low rank tensor approximation,
Dynamic magnetic resonance imaging
BibRef
Shetty, G.N.,
Slavakis, K.,
Bose, A.,
Nakarmi, U.,
Scutari, G.,
Ying, L.,
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery,
MedImg(39), No. 3, March 2020, pp. 688-702.
IEEE DOI
2004
Magnetic resonance imaging, Manifolds, Task analysis, Data models,
Image reconstruction, Dimensionality reduction,
dimensionality reduction
BibRef
Bliesener, Y.,
Acharya, J.,
Nayak, K.S.,
Efficient DCE-MRI Parameter and Uncertainty Estimation Using a Neural
Network,
MedImg(39), No. 5, May 2020, pp. 1712-1723.
IEEE DOI
2005
Quantitative imaging, DCE MRI, parameter estimation, uncertainty estimation
BibRef
Uus, A.,
Zhang, T.,
Jackson, L.H.,
Roberts, T.A.,
Rutherford, M.A.,
Hajnal, J.V.,
Deprez, M.,
Deformable Slice-to-Volume Registration for Motion Correction of
Fetal Body and Placenta MRI,
MedImg(39), No. 9, September 2020, pp. 2750-2759.
IEEE DOI
2009
Image reconstruction, Magnetic resonance imaging, Strain,
Shape, Image resolution, Estimation, MRI,
deformable registration
BibRef
Lee, H.,
Zhao, X.,
Song, H.K.,
Wehrli, F.W.,
Self-Navigated Three-Dimensional Ultrashort Echo Time Technique for
Motion-Corrected Skull MRI,
MedImg(39), No. 9, September 2020, pp. 2869-2880.
IEEE DOI
2009
Trajectory,
Magnetic resonance imaging, Bones, Image reconstruction,
k-space trajectory correction
BibRef
Shaw, R.,
Sudre, C.H.,
Varsavsky, T.,
Ourselin, S.,
Cardoso, M.J.,
A k-Space Model of Movement Artefacts: Application to Segmentation
Augmentation and Artefact Removal,
MedImg(39), No. 9, September 2020, pp. 2881-2892.
IEEE DOI
2009
Transforms, Machine learning,
Solid modeling, Image segmentation, Magnetic resonance imaging,
uncertainty
BibRef
Singh, A.,
Salehi, S.S.M.,
Gholipour, A.,
Deep Predictive Motion Tracking in Magnetic Resonance Imaging:
Application to Fetal Imaging,
MedImg(39), No. 11, November 2020, pp. 3523-3534.
IEEE DOI
2011
Magnetic resonance imaging, Tracking,
Pose estimation, Feature extraction, Dynamics, Head,
MRI
BibRef
Cheng, J.[Jing],
Cui, Z.X.[Zhuo-Xu],
Huang, W.Q.[Wen-Qi],
Ke, Z.W.[Zi-Wen],
Ying, L.[Leslie],
Wang, H.F.[Hai-Feng],
Zhu, Y.J.[Yan-Jie],
Liang, D.[Dong],
Learning Data Consistency and its Application to Dynamic MR Imaging,
MedImg(40), No. 11, November 2021, pp. 3140-3153.
IEEE DOI
2111
Image reconstruction, Imaging, Magnetic resonance imaging,
Data models, Training, Deep learning, Supervised learning,
dynamic magnetic resonance imaging
BibRef
Zhang, J.C.[Jia-Cheng],
Rothenberger, S.M.[Sean M.],
Brindise, M.C.[Melissa C.],
Scott, M.B.[Michael B.],
Berhane, H.[Haben],
Baraboo, J.J.[Justin J.],
Markl, M.[Michael],
Rayz, V.L.[Vitaliy L.],
Vlachos, P.P.[Pavlos P.],
Divergence-Free Constrained Phase Unwrapping and Denoising for 4D
Flow MRI Using Weighted Least-Squares,
MedImg(40), No. 12, December 2021, pp. 3389-3399.
IEEE DOI
2112
Magnetic resonance imaging, Uncertainty, Encoding, Wrapping,
Robustness, Phase measurement, In vitro,
weighted least-squares
BibRef
Ke, Z.[Ziwen],
Huang, W.Q.[Wen-Qi],
Cui, Z.X.[Zhuo-Xu],
Cheng, J.[Jing],
Jia, S.[Sen],
Wang, H.F.[Hai-Feng],
Liu, X.[Xin],
Zheng, H.R.[Hai-Rong],
Ying, L.[Leslie],
Zhu, Y.J.[Yan-Jie],
Liang, D.[Dong],
Learned Low-Rank Priors in Dynamic MR Imaging,
MedImg(40), No. 12, December 2021, pp. 3698-3710.
IEEE DOI
2112
Imaging, Image reconstruction, Learning systems, Transforms,
Sparse matrices, Magnetic resonance imaging, Deep learning,
model-based network
BibRef
Yoo, J.[Jaejun],
Jin, K.H.[Kyong Hwan],
Gupta, H.[Harshit],
Yerly, J.[Jérôme],
Stuber, M.[Matthias],
Unser, M.[Michael],
Time-Dependent Deep Image Prior for Dynamic MRI,
MedImg(40), No. 12, December 2021, pp. 3337-3348.
IEEE DOI
2112
Magnetic resonance imaging, Image reconstruction, Manifolds,
Electronics packaging, Imaging, Heuristic algorithms,
unsupervised learning
BibRef
Ma, S.L.[Shu-Li],
Fan, Y.C.[You-Chen],
Li, Z.F.[Zhi-Fei],
Dynamic MRI Exploiting Partial Separability and Shift Invariant
Discrete Wavelet Transform,
ICIVC21(242-246)
IEEE DOI
2112
Wavelet domain, Magnetic resonance imaging, Heuristic algorithms,
Frequency-domain analysis, Computational modeling,
ADMM
BibRef
Rothenberger, S.M.[Sean M.],
Zhang, J.C.[Jia-Cheng],
Brindise, M.C.[Melissa C.],
Schnell, S.[Susanne],
Markl, M.[Michael],
Vlachos, P.P.[Pavlos P.],
Rayz, V.L.[Vitaliy L.],
Modeling Bias Error in 4D Flow MRI Velocity Measurements,
MedImg(41), No. 7, July 2022, pp. 1802-1812.
IEEE DOI
2207
Magnetic resonance imaging, Velocity measurement,
Measurement uncertainty, Mathematical models, Spatial resolution,
systematic error
BibRef
Ahmed, A.H.[Abdul Haseeb],
Zou, Q.[Qing],
Nagpal, P.[Prashant],
Jacob, M.[Mathews],
Dynamic Imaging Using Deep Bi-Linear Unsupervised Representation
(DEBLUR),
MedImg(41), No. 10, October 2022, pp. 2693-2703.
IEEE DOI
2210
Magnetic resonance imaging, Generators, Image reconstruction,
Convolutional neural networks, Optimization, Noise measurement,
unsupervised learning
BibRef
Zou, J.[Jiaren],
Cao, Y.[Yue],
Joint Optimization of k-t Sampling Pattern and Reconstruction of DCE
MRI for Pharmacokinetic Parameter Estimation,
MedImg(41), No. 11, November 2022, pp. 3320-3331.
IEEE DOI
2211
Dynamic Contrast-Enhanced MRI.
Image reconstruction, Magnetic resonance imaging, Training,
Parameter estimation, Optimization, Spatial resolution, pharmacokinetic model
BibRef
Zou, Q.[Qing],
Ahmed, A.H.[Abdul Haseeb],
Nagpal, P.[Prashant],
Priya, S.[Sarv],
Schulte, R.F.[Rolf F.],
Jacob, M.[Mathews],
Variational Manifold Learning From Incomplete Data:
Application to Multislice Dynamic MRI,
MedImg(41), No. 12, December 2022, pp. 3552-3561.
IEEE DOI
2212
Magnetic resonance imaging, Manifolds, Data models,
Time series analysis, Convolutional neural networks, image reconstruction
BibRef
Djebra, Y.[Yanis],
Marin, T.[Thibault],
Han, P.K.[Paul K.],
Bloch, I.[Isabelle],
El Fakhri, G.[Georges],
Ma, C.[Chao],
Manifold Learning via Linear Tangent Space Alignment (LTSA) for
Accelerated Dynamic MRI With Sparse Sampling,
MedImg(42), No. 1, January 2023, pp. 158-169.
IEEE DOI
2301
Manifolds, Image reconstruction, Magnetic resonance imaging,
Mathematical models, Data models, Biomedical imaging, Transforms,
linear tangent space alignment (LTSA)
BibRef
Zaffrani-Reznikov, Y.[Yael],
Afacan, O.[Onur],
Kurugol, S.[Sila],
Warfield, S.[Simon],
Freiman, M.[Moti],
qdwi-morph: Motion-compensated Quantitative Diffusion-weighted MRI
Analysis for Fetal Lung Maturity Assessment,
MCV22(482-494).
Springer DOI
2304
BibRef
Rothenberger, S.M.[Sean M.],
Patel, N.M.[Neal M.],
Zhang, J.C.[Jia-Cheng],
Schnell, S.[Susanne],
Craig, B.A.[Bruce A.],
Ansari, S.A.[Sameer A.],
Markl, M.[Michael],
Vlachos, P.P.[Pavlos P.],
Rayz, V.L.[Vitaliy L.],
Automatic 4D Flow MRI Segmentation Using the Standardized Difference
of Means Velocity,
MedImg(42), No. 8, August 2023, pp. 2360-2373.
IEEE DOI
2308
Image segmentation, Magnetic resonance imaging,
Velocity measurement, Measurement, In vivo, In vitro,
phase contrast magnetic resonance imaging (PC-MRI)
BibRef
Zhi, S.H.[Shao-Hua],
Wang, Y.H.[Ying-Hui],
Xiao, H.[Haonan],
Bai, T.[Ti],
Li, B.[Bing],
Tang, Y.S.[Yun-Song],
Liu, C.Y.[Chen-Yang],
Li, W.[Wen],
Li, T.[Tian],
Ge, H.[Hong],
Cai, J.[Jing],
Coarse-Super-Resolution-Fine Network (CoSF-Net): A Unified End-to-End
Neural Network for 4D-MRI With Simultaneous Motion Estimation and
Super-Resolution,
MedImg(43), No. 1, January 2024, pp. 162-174.
IEEE DOI
2401
BibRef
Spieker, V.[Veronika],
Eichhorn, H.[Hannah],
Hammernik, K.[Kerstin],
Rueckert, D.[Daniel],
Preibisch, C.[Christine],
Karampinos, D.C.[Dimitrios C.],
Schnabel, J.A.[Julia A.],
Deep Learning for Retrospective Motion Correction in MRI:
A Comprehensive Review,
MedImg(43), No. 2, February 2024, pp. 846-859.
IEEE DOI
2402
Image reconstruction, Magnetic resonance imaging, Deep learning, Training,
Motion compensation, Motion detection, Loss measurement, deep learning
BibRef
Ortiz-Gonzalez, A.[Antonio],
Kobler, E.[Erich],
Simon, S.[Stefan],
Bischoff, L.[Leon],
Nowak, S.[Sebastian],
Isaak, A.[Alexander],
Block, W.[Wolfgang],
Sprinkart, A.M.[Alois M.],
Attenberger, U.[Ulrike],
Luetkens, J.A.[Julian A.],
Bayro-Corrochano, E.[Eduardo],
Effland, A.[Alexander],
Optical Flow-Guided Cine MRI Segmentation With Learned Corrections,
MedImg(43), No. 3, March 2024, pp. 940-953.
IEEE DOI
2403
Magnetic resonance imaging, Image segmentation,
Convolutional neural networks, Optical flow, Motion segmentation,
convolutional neural network
BibRef
Pan, J.Z.[Jia-Zhen],
Huang, W.Q.[Wen-Qi],
Rueckert, D.[Daniel],
Küstner, T.[Thomas],
Hammernik, K.[Kerstin],
Motion-Compensated MR CINE Reconstruction With Reconstruction-Driven
Motion Estimation,
MedImg(43), No. 7, July 2024, pp. 2420-2433.
IEEE DOI Code:
WWW Link.
2407
Image reconstruction, Motion estimation, Optimization, Imaging,
Estimation, Tuning, Training, Motion-compensated reconstruction,
reconstruction-driven registration/motion estimation
BibRef
Levilly, S.[Sébastien],
Moussaoui, S.[Saďd],
Serfaty, J.M.[Jean-Michel],
Segmentation-Free Velocity Field Super-Resolution on 4D Flow MRI,
IP(33), 2024, pp. 5637-5649.
IEEE DOI
2410
BibRef
Earlier:
Segmentation-Free Super-Resolved 4D flow MRI Reconstruction
Exploiting Navier-Stokes Equations and Spatial Regularization,
ICIP22(2316-2320)
IEEE DOI
2211
Magnetic resonance imaging, Vectors, Signal to noise ratio,
Image segmentation, Fluids, Superresolution, Velocity measurement,
spatial regularization.
Image resolution, Smoothing methods, Inverse problems, Shape,
Computational fluid dynamics, spatial regularization
BibRef
Vieira de Mello, J.P.[Jean Pablo],
Paixăo, T.M.[Thiago M.],
Berriel, R.[Rodrigo],
Reyes, M.[Mauricio],
Badue, C.[Claudine],
de Souza, A.F.[Alberto F.],
Oliveira-Santos, T.[Thiago],
Deep Learning-based Type Identification of Volumetric MRI Sequences,
ICPR21(1-8)
IEEE DOI
2105
Training, Deep learning, Protocols, Magnetic resonance imaging,
Manuals, Pattern recognition, Proposals
BibRef
Teixeira, J.F.[Joăo F.],
Bessa, S.[Sílvia],
Gouveia, P.F.[Pedro F.],
Oliveira, H.P.[Hélder P.],
A Framework for Fusion of T1-weighted and Dynamic MRI Sequences,
ICIAR20(II:157-169).
Springer DOI
2007
BibRef
Zhang, Z.Z.[Zi-Zhao],
Romero, A.[Adriana],
Muckley, M.J.[Matthew J.],
Vincent, P.[Pascal],
Yang, L.[Lin],
Drozdzal, M.[Michal],
Reducing Uncertainty in Undersampled MRI Reconstruction With Active
Acquisition,
CVPR19(2049-2053).
IEEE DOI
2002
BibRef
Corona, V.[Veronica],
Aviles-Rivero, A.I.[Angelica I.],
Debroux, N.[Noémie],
Graves, M.[Martin],
Le Guyader, C.[Carole],
Schönlieb, C.B.[Carola-Bibiane],
Williams, G.[Guy],
Multi-tasking to Correct:
Motion-Compensated MRI via Joint Reconstruction and Registration,
SSVM19(263-274).
Springer DOI
1909
BibRef
Kurugol, S.[Sila],
Marami, B.[Bahram],
Afacan, O.[Onur],
Warfield, S.K.[Simon K.],
Gholipour, A.[Ali],
Motion-Robust Spatially Constrained Parameter Estimation in Renal
Diffusion-Weighted MRI by 3D Motion Tracking and Correction of
Sequential Slices,
RAMBO17(75-85).
Springer DOI
1711
BibRef
Lin, X.X.,
Xia, L.Y.,
Liang, Y.,
Huang, H.H.,
Chai, H.,
Chan, K.F.,
Low-rank and sparse matrix decomposition based on S1/2 and L1/2
regularizations in dynamic MRI,
IPTA16(1-6)
IEEE DOI
1703
biomedical MRI
BibRef
Bones, P.,
MacLaren, J.,
Coping with motion in MRI: Developments since TRELLIS,
ICVNZ15(1-5)
IEEE DOI
1701
biomedical MRI
BibRef
Zhang, Y.,
Aganj, I.,
van der Kouwe, A.J.W.[André J.W.],
Tisdall, M.D.[M. Dylan],
Effects of Resolution and Registration Algorithm on the Accuracy of
EPI vNavs for Real Time Head Motion Correction in MRI,
WBIR16(583-591)
IEEE DOI
1612
BibRef
Ramos-Llorden, G.[Gabriel],
den Dekker, A.J.[Arnold J.],
van Steenkiste, G.[Gwendolyn],
van Audekerke, J.[Johan],
Verhoye, M.[Marleen],
Sijbers, J.[Jan],
Simultaneous motion correction and T1 estimation in quantitative T1
mapping: An ML restoration approach,
ICIP15(3160-3164)
IEEE DOI
1512
T1 mapping; alignment; motion estimation; registration; relaxometry
BibRef
Guyader, J.M.[Jean-Marie],
Huizinga, W.[Wyke],
Fortunati, V.,
Poot, D.H.J.[Dirk H. J.],
van Kranenburg, M.[Matthijs],
Veenland, J.F.,
Paulides, M.M.,
Niessen, W.J.[Wiro J.],
Klein, S.[Stefan],
Total Correlation-Based Groupwise Image Registration for Quantitative
MRI,
WBIR16(626-633)
IEEE DOI
1612
BibRef
Huizinga, W.[Wyke],
Poot, D.H.J.[Dirk H. J.],
Guyader, J.M.[Jean-Marie],
Smit, H.[Henk],
van Kranenburg, M.[Matthijs],
van Geuns, R.J.M.[Robert-Jan M.],
Uitterdijk, A.[André],
van Beusekom, H.M.M.[Heleen M. M.],
Coolen, B.F.[Bram F.],
Leemans, A.[Alexander],
Niessen, W.J.[Wiro J.],
Klein, S.[Stefan],
Non-rigid Groupwise Image Registration for Motion Compensation in
Quantitative MRI,
WBIR14(184-193).
Springer DOI
1407
BibRef
Gao, X.H.[Xiao-Hong],
Feature wise representation for both still and motion 3D medical
images,
Southwest14(1-4)
IEEE DOI
1406
biomedical MRI
BibRef
Mun, S.[Sungkwang],
Fowler, J.E.[James E.],
Motion-compensated compressed-sensing reconstruction for dynamic MRI,
ICIP13(1006-1010)
IEEE DOI
1402
Approximation methods
BibRef
Lu, Y.H.[Yan-Hong],
Yang, R.[Ran],
Super-resolution reconstruction of dynamic MRI by patch learning,
ICARCV12(1443-1448).
IEEE DOI
1304
BibRef
Sushma, M.,
Gupta, A.,
Sivaswamy, J.,
Time-frequency analysis based motion detection in perfusion weighted
MRI,
NCVPRIPG13(1-4)
IEEE DOI
1408
biomedical MRI
BibRef
Lin, Y.J.[Yu-Jun],
Zhuang, Q.[Qiaodi],
Yang, R.[Ran],
Image reconstruction of dynamic MRI based on adaptive motion estimation,
ICARCV12(1586-1590).
IEEE DOI
1304
BibRef
Gautam, R.[Rohit],
Sivaswamy, J.[Jayanthi],
Varma, R.[Ravi],
An efficient, bolus-stage based method for motion correction in
perfusion weighted MRI,
ICPR12(145-148).
WWW Link.
1302
BibRef
Su, H.R.[Hong-Ren],
Lee, T.Y.[Tung-Ying],
Lai, S.H.[Shang-Hong],
Chang, T.C.[Ti-Chiun],
MRI motion artifact correction based on spectral extrapolation with
generalized series,
ICIP10(1133-1136).
IEEE DOI
1009
BibRef
Earlier: A2, A1, A3, A4:
Compensation of motion artifacts in MRI via graph-based optimization,
CVPR09(2192-2199).
IEEE DOI
0906
BibRef
Raba, D.[David],
Peracaula, M.[Marta],
Martí, R.[Robert],
Martí, J.[Joan],
On the Detection of Regions-of-Interest in Dynamic Contrast-Enhanced
MRI,
IbPRIA07(I: 129-136).
Springer DOI
0706
BibRef
Rajguru, N.S.,
Rodriguez, J.J.,
Raghunand, N.,
Gillies, R.J.,
Enhanced Level-Set Approach to Segmentation of 3-D Heterogeneous
Lesions from Dynamic Contrast-Enhanced MR Images,
Southwest06(71-75).
IEEE DOI
0603
BibRef
Bystrov, D.[Daniel],
Pekar, V.[Vladimir],
Meetz, K.[Kirsten],
Schulz, H.[Heinrich],
Netsch, T.[Thomas],
Motion Compensation and Plane Tracking for Kinematic MR-Imaging,
CVBIA05(551-560).
Springer DOI
0601
BibRef
Fahmy, A.,
Tewfik, A.H.,
Kadah, Y.M.,
Robust Estimation of Planar Rigid Body Motion in Magnetic Resonance
Imaging,
ICIP00(Vol II: 487-490).
IEEE DOI
0008
BibRef
Kadah, Y.M.,
Hu, X.P.[Xiao-Ping],
Automatic suppression of spatially variant translational motion
artifacts in magnetic resonance imaging,
ICIP98(I: 24-28).
IEEE DOI
9810
BibRef
Tseng, Y.H.[Yen-Hao],
Hwang, J.N.[Jenq-Neng],
Yuan, C.[Chun],
Motion artifact correction of MRI via iterative inverse problem solving,
ICIP94(I: 871-875).
IEEE DOI
9411
BibRef
Smith, M.,
Zeng, J.,
Crawley, A.,
A moving target evaluating algorithms for removing MRI motion artifacts,
ICIP94(III: 45-48).
IEEE DOI
9411
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
MRI, Enhancement, Noise and Artifact Reduction .