21.11.4 Dynamic Magnetic Resonance Imaging, Motion in MRI

Chapter Contents (Back)
MRI. Dynamic MRI. Magnetic Resonance.
See also Kidney Disease, Tomography, CAT Analysis, Other Methods.

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


Zhang, Y.H.[Ying-Hao], Li, X.D.[Xiao-Di], Li, W.[Weihang], Hu, Y.[Yue],
Deep Unrolling Shrinkage Network for Dynamic MR Imaging,
ICIP23(1145-1149)
IEEE DOI Code:
WWW Link. 2312
BibRef

Levilly, S.[Sébastien], Moussaoui, S.[Saïd], Serfaty, J.M.[Jean-Michel],
Segmentation-Free Super-Resolved 4D flow MRI Reconstruction Exploiting Navier-Stokes Equations and Spatial Regularization,
ICIP22(2316-2320)
IEEE DOI 2211
Image resolution, Smoothing methods, Inverse problems, Shape, Magnetic resonance imaging, Computational fluid dynamics, spatial regularization BibRef

Vieira de Mello, J.P.[Jean Pablo], Paixão, 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.[João 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 .


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