Zoroofi, R.A.,
Sato, Y.,
Tamura, S.,
Naito, H.,
MRI artifact cancellation due to rigid motion in the imaging plane,
MedImg(15), No. 6, December 1996, pp. 768-784.
IEEE Top Reference.
0203
BibRef
Atkinson, D.,
Hill, D.L.G.,
Stoyle, P.N.R.,
Summers, P.E.,
Keevil, S.F.,
Automatic Correction of Motion Artifacts in Magnetic-Resonance
Images Using an Entropy Focus Criterion,
MedImg(16), No. 6, December 1997, pp. 903-910.
IEEE Top Reference.
9803
BibRef
Brinkmann, B.H.,
Manduca, A.,
Robb, R.A.,
Optimized Homomorphic Unsharp Masking for MR
Grayscale Inhomogeneity Correction,
MedImg(17), No. 2, April 1998, pp. 161-171.
IEEE Top Reference.
9808
BibRef
Manduca, A.,
Muthupillai, R.,
Rossman, P.J.,
Greenleaf, J.F.,
Ehman, R.L.,
Local wavelength estimation for magnetic resonance elastography,
ICIP96(III: 527-530).
IEEE DOI
9610
BibRef
Bajla, I.,
Hollander, I.,
Nonlinear Filtering of Magnetic Resonance Tomograms by
Geometry Driven Diffusion,
MVA(10), No. 5-6, April 1998, pp. 243-255.
Springer DOI
9805
BibRef
Bajla, I.,
Holländer, I.,
Locally adaptive conductance in geometry-driven-diffusion filtering of
magnetic resonance tomograms,
VISP(147), No. 3, 2000, pp. 271-282.
0008
BibRef
Bajla, I.[Ivan],
Holländer, I.[Igor],
Geometry-driven-diffusion filtering of magnetic resonance images using
model-based conductance,
MVA(12), No. 5, 2001, pp. 223-237.
Springer DOI
0103
BibRef
Weerasinghe, C.,
Yan, H.,
An Improved Algorithm for Rotational Motion Artifact Suppression
in MRI,
MedImg(17), No. 2, April 1998, pp. 310-317.
IEEE Top Reference.
9808
BibRef
Weerasinghe, C.,
Yan, H.,
Correction of Motion Artifacts in MRI Caused by Rotations at
Constant Angular Velocity,
SP(70), No. 2, October 1998, pp. 103-114.
9812
BibRef
Schomberg, H.,
Off-resonance correction of MR images,
MedImg(18), No. 6, June 1999, pp. 481-495.
IEEE Top Reference.
0110
BibRef
Deichmann, R.,
Wiesmann, F.,
Hillenbrand, C.,
Hahn, D.,
Haase, A.,
Contrast enhancement and artifact reduction in magnetization-prepared
MR angiography,
IJIST(10), No. 3, 1999, pp. 266-272.
BibRef
9900
Nowak, R.D.,
Wavelet-Based Rician Noise Removal for Magnetic Resonance Imaging,
IP(8), No. 10, October 1999, pp. 1408-1419.
IEEE DOI
BibRef
9910
Ahn, C.B.,
Song, Y.C.,
Park, D.J.,
Adaptive template filtering for signal-to-noise ratio enhancement in
magnetic resonance imaging,
MedImg(18), No. 6, June 1999, pp. 549-556.
IEEE Top Reference.
0110
BibRef
Weaver, J.B.[John B.],
Applications of monotonic noise reduction algorithms in fMRI, phase
estimation, and contrast enhancement,
IJIST(10), No. 2, 1999, pp. 177-185.
BibRef
9900
Bakir, T.,
Reeves, S.J.,
A filter design method for minimizing ringing in a region of interest
in MR spectroscopic images,
MedImg(19), No. 6, June 2000, pp. 585-600.
IEEE Top Reference.
0110
BibRef
Weerasinghe, C.[Chaminda],
Ji, L.[Lilian],
Yan, H.[Hong],
A new method for ROI extraction from motion affected MR images based on
suppression of artifacts in the image background,
SP(80), No. 5, May 2000, pp. 867-88.
0005
BibRef
Kao, Y.H.[Yi-Hsuan],
MacFall, J.R.,
Correction of MR k-space data corrupted by spike noise,
MedImg(19), No. 7, July 2000, pp. 671-680.
IEEE Top Reference.
0110
BibRef
Glowinski, A.,
Adam, G.,
Bucker, A.,
van Vaals, J.,
Gunther, R.W.,
A perspective on needle artifacts in MRI: an electromagnetic model for
experimentally separating susceptibility effects,
MedImg(19), No. 12, December 2000, pp. 1248-1252.
IEEE Top Reference.
0110
BibRef
Xu, Z.H.[Zhi-Hua],
Chan, A.K.,
Encoding with frames in MRI and analysis of the signal-to-noise ratio,
MedImg(21), No. 4, April 2002, pp. 332-342.
IEEE Top Reference.
0206
BibRef
Archibald, R.,
Gelb, A.,
A method to reduce the Gibbs ringing artifact in MRI scans while
keeping tissue boundary integrity,
MedImg(21), No. 4, April 2002, pp. 305-319.
IEEE Top Reference.
0206
BibRef
Archibald, R.,
Hu, J.,
Gelb, A.,
Farin, G.,
Improving the Accuracy of Volumetric Segmentation Using Pre-Processing
Boundary Detection and Image Reconstruction,
IP(13), No. 4, April 2004, pp. 459-466.
IEEE DOI
0404
BibRef
Bao, P.,
Zhang, L.[Lei],
Noise reduction for magnetic resonance images via adaptive multiscale
products thresholding,
MedImg(22), No. 9, September 2003, pp. 1089-1099.
IEEE Abstract.
0309
BibRef
Lysaker, M.,
Lundervold, A.,
Tai, X.C.[Xue-Cheng],
Noise removal using fourth-order partial differential equation with
applications to medical magnetic resonance images in space and time,
IP(12), No. 12, December 2003, pp. 1579-1590.
IEEE DOI
0402
BibRef
Winkelmann, S.,
Schaeffter, T.,
Eggers, H.,
Doessel, O.,
SNR Enhancement in Radial SSFP Imaging Using Partial k-Space Averaging,
MedImg(24), No. 2, February 2005, pp. 254-262.
IEEE Abstract.
0501
SSFP: steady-state free precessing. MRI sequences.
BibRef
Winkelmann, S.,
Schaeffter, T.,
Koehler, T.,
Eggers, H.,
Doessel, O.,
An Optimal Radial Profile Order Based on the Golden Ratio for
Time-Resolved MRI,
MedImg(26), No. 1, January 2007, pp. 68-76.
IEEE DOI
0701
BibRef
Madabhushi, A.[Anant],
Udupa, J.K.[Jayaram K.],
Interplay Between Intensity Standardization and Inhomogeneity
Correction in MR Image Processing,
MedImg(24), No. 5, May 2005, pp. 561-576.
IEEE Abstract.
0505
BibRef
Madabhushi, A.[Anant],
Udupa, J.K.[Jayaram K.],
Souza, A.[Andre],
Generalized scale: Theory, algorithms, and application to image
inhomogeneity correction,
CVIU(101), No. 2, February 2005, pp. 100-121.
Elsevier DOI
0512
BibRef
Ahmed, O.A.,
New Denoising Scheme for Magnetic Resonance Spectroscopy Signals,
MedImg(24), No. 6, June 2005, pp. 809-816.
IEEE Abstract.
0506
BibRef
Chang, Z.,
Xiang, Q.S.,
Nonlinear Phase Correction With an Extended Statistical Algorithm,
MedImg(24), No. 6, June 2005, pp. 791-798.
IEEE Abstract.
0506
MRI phase correction.
BibRef
Luo, J.,
Zhu, Y.,
Clarysse, P.,
Magnin, I.,
Correction of Bias Field in MR Images Using Singularity Function
Analysis,
MedImg(24), No. 8, August 2005, pp. 1067-1085.
IEEE DOI
0508
BibRef
Lin, W.,
Wehrli, F.W.,
Song, H.K.,
Correcting Bulk In-Plane Motion Artifacts in MRI Using the Point Spread
Function,
MedImg(24), No. 9, September 2005, pp. 1170-1176.
IEEE DOI
0509
BibRef
Pauchard, Y.,
Smith, M.R.,
Mintchev, M.P.,
Improving Geometric Accuracy in the Presence of Susceptibility
Difference Artifacts Produced by Metallic Implants in Magnetic
Resonance Imaging,
MedImg(24), No. 10, October 2005, pp. 1387-1399.
IEEE DOI
0510
BibRef
Kobashi, S.[Syoji],
Kondo, K.[Katsuya],
Hata, Y.[Yutaka],
Target image enhancement using representative line in MR
cholangiography images,
IJIST(14), No. 3, 2004, pp. 122-130.
DOI Link
0408
BibRef
Ibrahim, T.S.,
Ultrahigh-Field MRI Whole-Slice and Localized RF Field Excitations
Using the Same RF Transmit Array,
MedImg(25), No. 10, October 2006, pp. 1341-1347.
IEEE DOI
0609
BibRef
Khalidov, I.,
van de Ville, D.,
Jacob, M.,
Lazeyras, F.,
Unser, M.,
BSLIM: Spectral Localization by Imaging With Explicit B{0} Field
Inhomogeneity Compensation,
MedImg(26), No. 7, July 2007, pp. 990-1000.
IEEE DOI
0707
Magnetic resonance spectroscopy imaging (MRSI)
BibRef
Garcia-Sebastian, M.[Maite],
Fernandez, E.[Elsa],
Grana, M.[Manuel],
Torrealdea, F.J.[Francisco J.],
A parametric gradient descent MRI intensity inhomogeneity correction
algorithm,
PRL(28), No. 13, 1 October 2007, pp. 1657-1666.
Elsevier DOI
0709
MRI; Intensity inhomogeneity correction; Parametric methods
BibRef
Awate, S.P.,
Whitaker, R.T.,
Feature-Preserving MRI Denoising: A Nonparametric Empirical Bayes
Approach,
MedImg(26), No. 9, September 2007, pp. 1242-1255.
IEEE DOI
0710
BibRef
Hamarneh, G.,
Hradsky, J.,
Bilateral Filtering of Diffusion Tensor Magnetic Resonance Images,
IP(16), No. 10, October 2007, pp. 2463-2475.
IEEE DOI
0711
BibRef
Gilbert, G.,
Simard, D.,
Beaudoin, G.,
Impact of an Improved Combination of Signals From Array Coils in
Diffusion Tensor Imaging,
MedImg(26), No. 11, November 2007, pp. 1428-1436.
IEEE DOI
0709
BibRef
Latt, J.,
Nilsson, M.,
Malmborg, C.,
Rosquist, H.,
Wirestam, R.,
Stahlberg, F.,
Topgaard, D.,
Brockstedt, S.,
Accuracy of q-Space Related Parameters in MRI:
Simulations and Phantom Measurements,
MedImg(26), No. 11, November 2007, pp. 1437-1447.
IEEE DOI
0709
BibRef
Matter, N.I.,
Chronik, B.,
Pauly, J.M.,
Macovski, A.,
Conolly, S.M.,
Scott, G.C.,
Noise Performance of a Precision Pulsed Electromagnet Power Supply for
Magnetic Resonance Imaging,
MedImg(27), No. 1, January 2008, pp. 75-86.
IEEE DOI
0712
BibRef
Cukur, T.,
Santos, J.M.,
Pauly, J.M.,
Nishimura, D.G.,
Variable-Density Parallel Imaging With Partially Localized Coil
Sensitivities,
MedImg(29), No. 5, May 2010, pp. 1173-1181.
IEEE DOI
1006
BibRef
Coupe, P.,
Yger, P.,
Prima, S.,
Hellier, P.,
Kervrann, C.,
Barillot, C.,
An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic
Resonance Images,
MedImg(27), No. 4, April 2008, pp. 425-441.
IEEE DOI
0804
BibRef
Coupe, P.,
Hellier, P.,
Kervrann, C.,
Barillot, C.,
Nonlocal Means-Based Speckle Filtering for Ultrasound Images,
IP(18), No. 10, October 2009, pp. 2221-2229.
IEEE DOI
0909
BibRef
Aja-Fernandez, S.,
Alberola-Lopez, C.,
Westin, C.F.,
Noise and Signal Estimation in Magnitude MRI and Rician Distributed
Images: A LMMSE Approach,
IP(17), No. 8, August 2008, pp. 1383-1398.
IEEE DOI
0808
BibRef
Aja-Fernandez, S.[Santiago],
Niethammer, M.,
Kubicki, M.,
Shenton, M.E.,
Westin, C.F.,
Restoration of DWI Data Using a Rician LMMSE Estimator,
MedImg(27), No. 10, October 2008, pp. 1389-1403.
IEEE DOI
0810
Diffusion weighted magnetic resonance imaging.
BibRef
Yuan, Y.,
Zhu, H.,
Ibrahim, J.G.,
Lin, W.,
Peterson, B.G.,
A Note on the Validity of Statistical Bootstrapping for Estimating the
Uncertainty of Tensor Parameters in Diffusion Tensor Images,
MedImg(27), No. 10, October 2008, pp. 1506-1514.
IEEE DOI
0810
BibRef
He, L.,
Greenshields, I.R.,
A Nonlocal Maximum Likelihood Estimation Method for Rician Noise
Reduction in MR Images,
MedImg(28), No. 2, February 2009, pp. 165-172.
IEEE DOI
0902
BibRef
Knopp, T.,
Eggers, H.,
Dahnke, H.,
Prestin, J.,
Senegas, J.,
Iterative Off-Resonance and Signal Decay Estimation and Correction for
Multi-Echo MRI,
MedImg(28), No. 3, March 2009, pp. 394-404.
IEEE DOI
0903
BibRef
Nguyen, H.M.,
Sutton, B.P.,
Morrison, Jr., R.L.,
Do, M.N.,
Joint Estimation and Correction of Geometric Distortions for EPI
Functional MRI Using Harmonic Retrieval,
MedImg(28), No. 3, March 2009, pp. 423-434.
IEEE DOI
0903
BibRef
Chou, H.F.[Hsiao-Fang],
Younes, L.[Laurent],
Smoothing Directional Vector Fields Using Dual Norms,
SIIMS(2), No. 1, 2009, pp. 41-63.
diffusion tensor imaging; magnetic resonance imaging; noise removal;
tensor; diffusion tensor interpolation
DOI Link
BibRef
0900
Krissian, K.,
Aja-Fernandez, S.,
Noise-Driven Anisotropic Diffusion Filtering of MRI,
IP(18), No. 10, October 2009, pp. 2265-2274.
IEEE DOI
0909
See also Flux-based anisotropic diffusion applied to enhancement of 3-D angiogram.
BibRef
Maitra, R.,
Faden, D.,
Noise Estimation in Magnitude MR Datasets,
MedImg(28), No. 10, October 2009, pp. 1615-1622.
IEEE DOI
0910
BibRef
Hsu, Y.C.,
Hsu, C.H.,
Tseng, W.Y.I.,
Correction for Susceptibility-Induced Distortion in Echo-Planar Imaging
Using Field Maps and Model-Based Point Spread Function,
MedImg(28), No. 11, November 2009, pp. 1850-1857.
IEEE DOI
0911
BibRef
Gur, Y.[Yaniv],
Pasternak, O.[Ofer],
Sochen, N.A.[Nir A.],
Fast GL(n)-Invariant Framework for Tensors Regularization,
IJCV(85), No. 3, December 2009, pp. xx-yy.
Springer DOI
0911
BibRef
Gur, Y.[Yaniv],
Sochen, N.A.[Nir A.],
Fast Invariant Riemannian DT-MRI Regularization,
MMBIA07(1-7).
IEEE DOI
0710
BibRef
Poot, D.H.J.,
den Dekker, A.J.,
Achten, E.,
Verhoye, M.,
Sijbers, J.[Jan],
Optimal Experimental Design for Diffusion Kurtosis Imaging,
MedImg(29), No. 3, March 2010, pp. 819-829.
IEEE DOI
1003
MRI model for non-Gaussian diffusion in tissue.
BibRef
Ramos-Llorden, G.[Gabriel],
Segers, H.[Hilde],
Palenstijn, W.J.[Willem Jan],
den Dekker, A.J.[Arnold J.],
Sijbers, J.[Jan],
Partially discrete magnetic resonance tomography,
ICIP15(1653-1657)
IEEE DOI
1512
Bayesian segmentation
BibRef
Qi, L.Q.[Li-Qun],
Yu, G.H.[Gao-Hang],
Wu, E.X.[Ed X.],
Higher Order Positive Semidefinite Diffusion Tensor Imaging,
SIIMS(3), No. 3, 2010, pp. 416-433.
DOI Link positive semidefinite diffusion tensor; apparent diffusion
coefficient; Z-eigenvalue; convex optimization problem; invariants
BibRef
1000
Qi, L.Q.[Li-Qun],
Yu, G.H.[Gao-Hang],
Xu, Y.[Yi],
Nonnegative Diffusion Orientation Distribution Function,
JMIV(45), No. 2, February 2013, pp. 103-113.
WWW Link.
1302
BibRef
Khademi, A.,
Venetsanopoulos, A.,
Moody, A.R.,
Image Enhancement and Noise Suppression for FLAIR MRIs With White
Matter Lesions,
SPLetters(17), No. 12, December 2010, pp. 989-992.
IEEE DOI
1011
BibRef
Dowson, N.[Nicholas],
Salvado, O.[Olivier],
Hashed Nonlocal Means for Rapid Image Filtering,
PAMI(33), No. 3, March 2011, pp. 485-499.
IEEE DOI
1102
3-D data noise filtering. Retain structure.
BibRef
Ozcan, A.[Aydogan],
Minimization of Imaging Gradient Effects in Diffusion Tensor Imaging,
MedImg(30), No. 3, March 2011, pp. 642-654.
IEEE DOI
1103
BibRef
Puy, G.,
Vandergheynst, P.,
Wiaux, Y.,
On Variable Density Compressive Sampling,
SPLetters(18), No. 10, October 2011, pp. 595-598.
IEEE DOI
1109
BibRef
Davies, M.,
Puy, G.,
Vandergheynst, P.,
Wiaux, Y.,
A Compressed Sensing Framework for Magnetic Resonance Fingerprinting,
SIIMS(7), No. 4, 2014, pp. 2623-2656.
DOI Link
1412
BibRef
Puy, G.,
Marques, J.P.,
Gruetter, R.,
Thiran, J.P.,
van de Ville, D.,
Vandergheynst, P.,
Wiaux, Y.,
Spread Spectrum Magnetic Resonance Imaging,
MedImg(31), No. 3, March 2012, pp. 586-598.
IEEE DOI
1203
BibRef
Kim, D.W.[Dong Wook],
Kim, C.[Chansoo],
Kim, D.H.[Dong Hee],
Lim, D.H.[Dong Hoon],
Rician nonlocal means denoising for MR images using nonparametric
principal component analysis,
JIVP(2011), No. 1 2011, pp. xx-yy.
DOI Link
1203
BibRef
Ramani, S.,
Liu, Z.,
Rosen, J.,
Nielsen, J.F.,
Fessler, J.A.,
Regularization Parameter Selection for Nonlinear Iterative Image
Restoration and MRI Reconstruction Using GCV and SURE-Based Methods,
IP(21), No. 8, August 2012, pp. 3659-3672.
IEEE DOI
1208
BibRef
Matakos, A.,
Ramani, S.,
Fessler, J.A.,
Accelerated Edge-Preserving Image Restoration Without Boundary
Artifacts,
IP(22), No. 5, May 2013, pp. 2019-2029.
IEEE DOI
1304
BibRef
Ramani, S.,
Weller, D.S.,
Nielsen, J.F.,
Fessler, J.A.,
Non-Cartesian MRI Reconstruction With Automatic Regularization Via
Monte-Carlo SURE,
MedImg(32), No. 8, 2013, pp. 1411-1422.
IEEE DOI
1307
Image reconstruction
BibRef
Weller, D.S.,
Reconstruction with dictionary learning for accelerated parallel
magnetic resonance imaging,
Southwest16(105-108)
IEEE DOI
1605
Compressed sensing
BibRef
Luisier, F.,
Blu, T.,
Wolfe, P.J.,
A CURE for Noisy Magnetic Resonance Images:
Chi-Square Unbiased Risk Estimation,
IP(21), No. 8, August 2012, pp. 3454-3466.
IEEE DOI
1208
BibRef
Coupe, P.,
Manjon, J.V.,
Robles, M.,
Collins, D.L.,
Adaptive multiresolution non-local means filter for three-dimensional
magnetic resonance image denoising,
IET-IPR(6), No. 5, 2012, pp. 558-568.
DOI Link
1210
BibRef
Yap, P.T.[Pew-Thian],
Shen, D.G.[Ding-Gang],
Spatial Transformation of DWI Data Using Non-Negative Sparse
Representation,
MedImg(31), No. 11, November 2012, pp. 2035-2049.
IEEE DOI
1211
BibRef
Earlier:
DWI Denoising Using Spatial, Angular, and Radiometric Filtering,
MBIA12(194-202).
Springer DOI
1210
BibRef
Duits, R.[Remco],
Haije, T.C.J.D.[Tom C.J. Dela],
Creusen, E.J.[Eric J.],
Ghosh, A.[Arpan],
Morphological and Linear Scale Spaces for Fiber Enhancement in DW-MRI,
JMIV(46), No. 3, July 2013, pp. 326-368.
Springer DOI
1306
BibRef
And:
Erratum:
JMIV(46), No. 3, July 2013, pp. 369.
Springer DOI
1306
BibRef
Earlier: A3, A1, A2, Only:
Numerical Schemes for Linear and Non-linear Enhancement of DW-MRI,
SSVM11(14-25).
Springer DOI
1201
BibRef
Duits, R.[Remco],
Haije, T.C.J.D.[Tom C.J. Dela],
Ghosh, A.[Arpan],
Creusen, E.[Eric],
Vilanova, A.[Anna],
ter Haar Romeny, B.M.[Bart M.],
Fiber Enhancement in Diffusion-Weighted MRI,
SSVM11(1-13).
Springer DOI
1201
BibRef
Dolui, S.[Sudipto],
Kuurstra, A.[Alan],
Patarroyo, I.C.S.[Iván C. Salgado],
Michailovich, O.V.[Oleg V.],
A new similarity measure for non-local means filtering of MRI images,
JVCIR(24), No. 7, 2013, pp. 1040-1054.
Elsevier DOI
1309
Magnetic resonance imaging
BibRef
Banerjee, A.[Abhirup],
Maji, P.[Pradipta],
Rough Sets for Bias Field Correction in MR Images Using
Contraharmonic Mean and Quantitative Index,
MedImg(32), No. 11, 2013, pp. 2140-2151.
IEEE DOI
1312
BibRef
Earlier:
Rough Set Based Homogeneous Unsharp Masking for Bias Field Correction
in MRI,
CIAP13(II:542-551).
Springer DOI
1309
BibRef
Earlier:
Contraharmonic Mean Based Bias Field Correction in MR Images,
CAIP13(523-530).
Springer DOI
1308
approximation theory
BibRef
Banerjee, A.[Abhirup],
Maji, P.[Pradipta],
Rough Sets and Stomped Normal Distribution for Simultaneous
Segmentation and Bias Field Correction in Brain MR Images,
IP(24), No. 12, December 2015, pp. 5764-5776.
IEEE DOI
1512
biological tissues
BibRef
Banerjee, A.[Abhirup],
Maji, P.[Pradipta],
Spatially Constrained Student's t-Distribution Based Mixture Model for
Robust Image Segmentation,
JMIV(60), No. 3, March 2018, pp. 355-381.
Springer DOI
1804
BibRef
Paul, J.S.[Joseph Suresh],
Mathew, J.J.[Joshin John],
Kesavadas, C.[Chandrasekhar],
MR image enhancement using an extended neighborhood filter,
JVCIR(25), No. 7, 2014, pp. 1604-1615.
Elsevier DOI
1410
Contrast enhancement
BibRef
Mathew, J.J.[Joshin John],
James, A.[Alex],
Kesavadas, C.[Chandrasekhar],
Paul, J.S.[Joseph Suresh],
Diffusion sensitivity enhancement filter for raw DWIs,
IET-CV(12), No. 7, October 2018, pp. 950-956.
DOI Link
1809
BibRef
Yang, S.[Shuo],
Li, J.X.[Jian-Xun],
The design of composite adaptive morphological filter and
applications to Rician noise reduction in MR images,
IJIST(25), No. 1, 2015, pp. 15-23.
DOI Link
1502
input-adaptive morphology
BibRef
Algarin, J.M.,
Breuer, F.,
Behr, V.C.,
Freire, M.J.,
Analysis of the Noise Correlation in MRI Coil Arrays Loaded With
Metamaterial Magnetoinductive Lenses,
MedImg(34), No. 5, May 2015, pp. 1148-1154.
IEEE DOI
1505
Coils
BibRef
Lee, D.H.[Dong-Hoon],
Hong, C.[Cheolpyo],
Lee, M.W.[Man-Woo],
Han, B.S.[Bong-Soo],
Signal intensity correction for multichannel MR images using radon
transformation,
IJIST(25), No. 2, 2015, pp. 148-152.
DOI Link
1506
intensity correction
BibRef
Lee, D.H.[Dong-Hoon],
Lee, D.W.[Do-Wan],
Han, B.S.[Bong-Soo],
Simple image intensity compensation (SIMIC) method prior to
application of distortion correction algorithms in brain diffusion
Tensor Magnetic Resonance Imaging: Validation test for two cost
functions of distortion correction algorithms,
IJIST(25), No. 4, 2015, pp. 328-333.
DOI Link
1512
distortion correction
BibRef
Wundrak, S.,
Paul, J.,
Ulrici, J.,
Hell, E.,
Rasche, V.,
A Small Surrogate for the Golden Angle in Time-Resolved Radial MRI
Based on Generalized Fibonacci Sequences,
MedImg(34), No. 6, June 2015, pp. 1262-1269.
IEEE DOI
1506
Fibonacci sequences
BibRef
Kumar, P.K.[P. Krishna],
Darshan, P.,
Kumar, S.[Sheethal],
Ravindra, R.[Rahul],
Rajan, J.[Jeny],
Saba, L.[Luca],
Suri, J.S.[Jasjit S.],
Magnetic resonance image denoising using nonlocal maximum likelihood
paradigm in DCT-framework,
IJIST(25), No. 3, 2015, pp. 256-264.
DOI Link
1509
MRI, noise, denoising, NLML, discrete cosine transform
BibRef
Sudeep, P.V.,
Palanisamy, P.,
Kesavadas, C.[Chandrasekharan],
Sijbers, J.[Jan],
den Dekker, A.J.[Arnold J.],
Rajan, J.[Jeny],
A nonlocal maximum likelihood estimation method for enhancing magnetic
resonance phase maps,
SIViP(11), No. 5, July 2017, pp. 913-920.
Springer DOI
1706
BibRef
Sudeep, P.V.,
Palanisamy, P.,
Kesavadas, C.[Chandrasekharan],
Rajan, J.[Jeny],
An improved nonlocal maximum likelihood estimation method for
denoising magnetic resonance images with spatially varying noise
levels,
PRL(139), 2020, pp. 34-41.
Elsevier DOI
2011
Denoising, Magnetic resonance imaging,
Maximum likelihood estimation, Nonlocal method, Parallel MRI,
Rician distribution
BibRef
Riji, R.,
Rajan, J.[Jeny],
Sijbers, J.[Jan],
Nair, M.S.[Madhu S.],
Iterative bilateral filter for Rician noise reduction in MR images,
SIViP(9), No. 7, October 2015, pp. 1543-1548.
WWW Link.
1509
BibRef
Shi, F.[Feng],
Cheng, J.[Jian],
Wang, L.[Li],
Yap, P.T.[Pew-Thian],
Shen, D.G.[Ding-Gang],
LRTV: MR Image Super-Resolution With Low-Rank and Total Variation
Regularizations,
MedImg(34), No. 12, December 2015, pp. 2459-2466.
IEEE DOI
1601
biomedical MRI
BibRef
Kwon, K.[Kinam],
Kim, D.C.[Dong-Chan],
Park, H.W.[Hyun-Wook],
Multi-contrast MR image denoising for parallel imaging using
multilayer perceptron,
IJIST(26), No. 1, 2016, pp. 65-75.
DOI Link
1604
denoising
BibRef
Palamodov, V.,
A Method of Reduction of Artifacts of Quantitative Susceptibility
Mapping,
SIIMS(9), No. 1, 2016, pp. 481-489.
DOI Link
1604
BibRef
Liu, H.,
Koonen, J.,
Fuderer, M.,
Heynderickx, I.,
The Relative Impact of Ghosting and Noise on the Perceived Quality of
MR Images,
IP(25), No. 7, July 2016, pp. 3087-3098.
IEEE DOI
1606
biomedical MRI
BibRef
Schmidt, R.,
Webb, A.,
Improvements in RF Shimming in High Field MRI Using High Permittivity
Materials With Low Order Pre-Fractal Geometries,
MedImg(35), No. 8, August 2016, pp. 1837-1844.
IEEE DOI
1608
Geometry
BibRef
Heydari, M.[Mostafa],
Karami, M.R.[Mohammad-Reza],
Babakhani, A.[Azizollah],
A new adaptive coupled diffusion PDE for MRI Rician noise,
SIViP(10), No. 7, October 2016, pp. 1211-1218.
Springer DOI
1609
BibRef
Bouhrara, M.,
Bonny, J.M.,
Ashinsky, B.G.,
Maring, M.C.,
Spencer, R.G.,
Noise Estimation and Reduction in Magnetic Resonance Imaging Using a
New Multispectral Nonlocal Maximum-likelihood Filter,
MedImg(36), No. 1, January 2017, pp. 181-193.
IEEE DOI
1701
Brain
BibRef
Martín, A.[Adrián],
Schiavi, E.[Emanuele],
Segura de León, S.[Sergio],
On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image
Rician Denoising,
JMIV(57), No. 2, February 2017, pp. 202-224.
Springer DOI
1702
BibRef
Zhang, X.[Xue],
Hou, L.[Likun],
Gao, H.[Hao],
Zhang, X.[Xiaoqun],
CUSTOM: A Calibration Region Recovery Approach for Highly Subsampled
Dynamic Parallel Magnetic Resonance Imaging,
JMIV(57), No. 3, March 2017, pp. 366-380.
WWW Link.
1702
BibRef
Upadhya, A.H.K.[Adithya H. K.],
Talawar, B.[Basavaraj],
Rajan, J.[Jeny],
GPU implementation of non-local maximum likelihood estimation method
for denoising magnetic resonance images,
RealTimeIP(13), No. 1, March 2017, pp. 181-192.
Springer DOI
1704
BibRef
Yeganli, S.F.[S. Faegheh],
Demirel, H.[Hasan],
Yu, R.[Runyi],
Noise removal from MR images via iterative regularization based on
higher-order singular value decomposition,
SIViP(11), No. 8, November 2017, pp. 1477-1484.
WWW Link.
1710
BibRef
Howison, M.[Mark],
Bethel, E.W.[E. Wes],
GPU-accelerated denoising of 3D magnetic resonance images,
RealTimeIP(13), No. 4, December 2017, pp. 713-724.
Springer DOI
1712
BibRef
Macdonald, J.[Jan],
Ruthotto, L.[Lars],
Improved Susceptibility Artifact Correction of Echo-Planar MRI using
the Alternating Direction Method of Multipliers,
JMIV(60), No. 2, February 2018, pp. 268-282.
Springer DOI
1802
BibRef
Romdhane, F.[Feriel],
Benzarti, F.[Faouzi],
Amiri, H.[Hamid],
A new method for three-dimensional magnetic resonance images denoising,
IJCVR(8), No. 1, 2018, pp. 1-17.
DOI Link
1804
BibRef
Kong, Z.,
Han, L.,
Liu, X.,
Yang, X.,
A New 4-D Nonlocal Transform-Domain Filter for 3-D Magnetic Resonance
Images Denoising,
MedImg(37), No. 4, April 2018, pp. 941-954.
IEEE DOI
1804
Collaboration, Image denoising, Noise reduction, Tensile stress,
Transforms, tensor-SVD
BibRef
Lobos, R.A.,
Kim, T.H.,
Hoge, W.S.,
Haldar, J.P.,
Navigator-Free EPI Ghost Correction With Structured Low-Rank Matrix
Models: New Theory and Methods,
MedImg(37), No. 11, November 2018, pp. 2390-2402.
IEEE DOI
1811
Imaging, Image reconstruction, Navigation, Data models, Convolution,
Eddy currents, Terminology, Echo-planar imaging, ghost correction,
constrained image reconstruction
BibRef
Granata, D.[Donatella],
Amato, U.[Umberto],
Alfano, B.[Bruno],
MRI denoising by nonlocal means on multi-GPU,
RealTimeIP(16), No. 2, April 2019, pp. 523-533.
WWW Link.
1904
BibRef
Kollem, S.[Sreedhar],
Reddy, K.R.L.[Katta Rama Linga],
Rao, D.S.[Duggirala Srinivasa],
Denoising and segmentation of MR images using fourth order non-linear
adaptive PDE and new convergent clustering,
IJIST(29), No. 3, September 2019, pp. 195-209.
DOI Link
1908
BibRef
Gao, Y.,
Liu, Y.,
Wang, Y.,
Shi, Z.,
Yu, J.,
A Universal Intensity Standardization Method Based on a Many-to-One
Weak-Paired Cycle Generative Adversarial Network for Magnetic
Resonance Images,
MedImg(38), No. 9, September 2019, pp. 2059-2069.
IEEE DOI
1909
Histograms, Convolution, Standardization,
Generative adversarial networks, Magnetic resonance imaging,
weak-pair strategy
BibRef
Chen, G.,
Dong, B.,
Zhang, Y.,
Lin, W.,
Shen, D.,
Yap, P.,
Denoising of Diffusion MRI Data via Graph Framelet Matching in x-q
Space,
MedImg(38), No. 12, December 2019, pp. 2838-2848.
IEEE DOI
1912
Noise reduction, Magnetic resonance imaging,
Signal to noise ratio, Transforms, White matter, Convolution,
neighborhood matching
BibRef
Nagarajan, I.,
Priya, G.G.L.[G.G. Lakshmi],
Removal of noise in MRI images using a block difference-based
filtering approach,
IJIST(30), No. 1, 2020, pp. 203-215.
DOI Link
2002
denoising, filtering, MRI, pixel similarity, Rician noise
BibRef
Chaabene, S.[Siwar],
Chaari, L.[Lotfi],
Kallel, A.[Abdelaziz],
Bayesian sparse regularization for parallel MRI reconstruction using
complex Bernoulli-Laplace mixture priors,
SIViP(14), No. 3, April 2020, pp. 445-453.
WWW Link.
2004
BibRef
Chaari, L.[Lotfi],
Benazza-Benyahia, A.[Amel],
Pesquet, J.C.[Jean-Christophe],
Ciuciu, P.[Philippe],
Wavelet-based parallel MRI regularization using bivariate sparsity
promoting priors,
ICIP09(1725-1728).
IEEE DOI
0911
BibRef
Kofler, A.,
Dewey, M.,
Schaeffter, T.,
Wald, C.,
Kolbitsch, C.,
Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction
for 2D Radial Cine MRI With Limited Training Data,
MedImg(39), No. 3, March 2020, pp. 703-717.
IEEE DOI
2004
Magnetic resonance imaging, Image reconstruction, Image sequences, Training,
persistent homology analysis
BibRef
Tripathi, P.C.[Prasun Chandra],
Bag, S.[Soumen],
CNN-DMRI: A Convolutional Neural Network for Denoising of Magnetic
Resonance Images,
PRL(135), 2020, pp. 57-63.
Elsevier DOI
2006
Convolutional Neural Network, Denoising, Encoder-decoder,
Magnetic Resonance Imaging, Residual learning
BibRef
Liu, S.,
Thung, K.,
Lin, W.,
Yap, P.,
Shen, D.,
Real-Time Quality Assessment of Pediatric MRI via Semi-Supervised
Deep Nonlocal Residual Neural Networks,
IP(29), 2020, pp. 7697-7706.
IEEE DOI
2007
Training, Semisupervised learning, Standards, Quality assessment,
Annotations, Deep learning, Kernel, Image quality assessment,
self-training
BibRef
George, M.M.[Maryjo M.],
Kalaivani, S.,
A diffusion-based compensation approach for intensity inhomogeneity
correction in MRI,
IJIST(30), No. 3, 2020, pp. 761-778.
DOI Link
2008
anisotropic diffusion filter, bias field, fuzzy c-means,
intensity inhomogeneity, MRI
BibRef
Lyu, Q.,
Shan, H.,
Steber, C.,
Helis, C.,
Whitlow, C.,
Chan, M.,
Wang, G.,
Multi-Contrast Super-Resolution MRI Through a Progressive Network,
MedImg(39), No. 9, September 2020, pp. 2738-2749.
IEEE DOI
2009
Image resolution, Magnetic resonance imaging, Signal resolution,
Feature extraction, Generators, Convolution,
progressive neural network
BibRef
Qiu, X.Q.[Xiao-Qun],
Chen, Z.[Zhen],
Adnan, S.[Saifullah],
He, H.W.[Hong-Wei],
Improved MR image denoising via low- rank approximation and
Laplacian-of-Gaussian edge detector,
IET-IPR(14), No. 12, October 2020, pp. 2791-2798.
DOI Link
2010
BibRef
Liu, S.,
Thung, K.H.,
Lin, W.,
Shen, D.,
Yap, P.T.,
Hierarchical Nonlocal Residual Networks for Image Quality Assessment
of Pediatric Diffusion MRI With Limited and Noisy Annotations,
MedImg(39), No. 11, November 2020, pp. 3691-3702.
IEEE DOI
2011
Feature extraction, Noise measurement, Data models,
Semisupervised learning, Residual neural networks, Image quality,
self-training
BibRef
Zhao, X.L.[Xiao-Le],
Hu, X.F.[Xia-Fei],
Liao, Y.[Ying],
He, T.[Tian],
Zhang, T.[Tao],
Zou, X.M.[Xue-Ming],
Tian, J.S.[Jin-Sha],
Accurate MR image super-resolution via lightweight lateral inhibition
network,
CVIU(201), 2020, pp. 103075.
Elsevier DOI
2011
Convolutional neural network, Deep learning,
Lateral inhibition, Magnetic resonance imaging, Super-resolution
BibRef
Wu, H.T.,
Zheng, K.,
Huang, Q.,
Hu, J.,
Contrast Enhancement of Multiple Tissues in MR Brain Images With
Reversibility,
SPLetters(28), 2021, pp. 160-164.
IEEE DOI
2102
Image segmentation, Histograms, Brain, Image enhancement,
Signal processing algorithms, Image restoration, reversible data hiding
BibRef
Shen, L.,
Zhu, W.,
Wang, X.,
Xing, L.,
Pauly, J.M.,
Turkbey, B.,
Harmon, S.A.,
Sanford, T.H.,
Mehralivand, S.,
Choyke, P.L.,
Wood, B.J.,
Xu, D.,
Multi-Domain Image Completion for Random Missing Input Data,
MedImg(40), No. 4, April 2021, pp. 1113-1122.
IEEE DOI
2104
Image segmentation, Tumors, Task analysis, Image synthesis,
Magnetic resonance imaging, Image reconstruction,
medical image synthesis
BibRef
Hadri, A.[Aissam],
Laghrib, A.[Amine],
Oummi, H.[Hssaine],
An optimal variable exponent model for Magnetic Resonance Images
denoising,
PRL(151), 2021, pp. 302-309.
Elsevier DOI
2110
MRI denoising, PDE-constrained optimization, Variable exponent, Primal- dual
BibRef
Fu, B.[Bo],
Dong, Y.H.[Yu-Han],
Fu, S.L.[Shi-Lin],
Mao, Y.X.[Yuan-Xin],
Thanh, D.N.H.[Dang N. H.],
Learning domain transfer for unsupervised magnetic resonance imaging
restoration and edge enhancement,
IJIST(32), No. 1, 2022, pp. 144-154.
DOI Link
2201
domain transfer, image deblurring, image denoising, MRI images,
unsupervised learning
BibRef
Su, J.S.[Jia-Sheng],
Pellicer-Guridi, R.[Ruben],
Edwards, T.[Thomas],
Fuentes, M.[Miguel],
Rosen, M.S.[Matthew S.],
Vegh, V.[Viktor],
Reutens, D.[David],
A CNN Based Software Gradiometer for Electromagnetic Background Noise
Reduction in Low Field MRI Applications,
MedImg(41), No. 5, May 2022, pp. 1007-1016.
IEEE DOI
2205
Coils, Magnetic resonance imaging, Sensitivity, Noise measurement,
Software, Convolutional neural networks,
ultra-low field magnetic resonance imaging
BibRef
Shukla, V.[Vedant],
Khandekar, P.[Prasad],
Khaparde, A.[Arti],
Estimation of Nonhomogeneous Noise in 2D Magnetic Resonance Imaging,
IJIST(32), No. 4, 2022, pp. 1357-1372.
DOI Link
2207
discrete wavelet transform (DWT), Gaussian noise (GN),
magnetic resonance imaging (MRI), noise estimation,
Sobel edge map
BibRef
Kollem, S.[Sreedhar],
Reddy, K.R.[Katta Ramalinga],
Rao, D.S.[Duggirala Srinivasa],
Prasad, C.R.[Chintha Rajendra],
Malathy, V.,
Ajayan, J.,
Muchahary, D.[Deboraj],
Image denoising for magnetic resonance imaging medical images using
improved generalized cross-validation based on the diffusivity
function,
IJIST(32), No. 4, 2022, pp. 1263-1285.
DOI Link
2207
adaptive Bayesian threshold, fourth-order partial differential equation,
quaternion wavelet transform
BibRef
Zhang, L.[Le],
Bronik, K.[Kevin],
Papiez, B.W.[Bartlomiej W.],
Learning to restore multiple image degradations simultaneously,
PR(136), 2023, pp. 109250.
Elsevier DOI
2301
Image restoration, Image quality, Multiple degradations, MRI
BibRef
Chung, H.J.[Hyung-Jin],
Lee, E.S.[Eun Sun],
Ye, J.C.[Jong Chul],
MR Image Denoising and Super-Resolution Using Regularized Reverse
Diffusion,
MedImg(42), No. 4, April 2023, pp. 922-934.
IEEE DOI
2304
Noise reduction, Noise measurement, Magnetic resonance imaging,
Mathematical models, Training, Diffusion processes, MRI
BibRef
Huang, P.Z.[Pei-Zhou],
Zhang, C.Y.[Chao-Yi],
Zhang, X.L.[Xiao-Liang],
Li, X.J.[Xiao-Juan],
Dong, L.[Liang],
Ying, L.[Leslie],
Self-Supervised Deep Unrolled Reconstruction Using Regularization by
Denoising,
MedImg(43), No. 3, March 2024, pp. 1203-1213.
IEEE DOI
2403
Image reconstruction, Noise reduction, Magnetic resonance imaging,
Training, Imaging, Training data, regularization by denoising
BibRef
Wu, J.[Jingpu],
Huang, Q.Q.[Qian-Qi],
Shen, Y.Q.[Yi-Qing],
Guo, P.F.[Peng-Fei],
Zhou, J.[Jinyuan],
Jiang, S.S.[Shan-Shan],
Radiomic feature reliability of amide proton transfer-weighted MR
images acquired with compressed sensing at 3?T,
IJIST(34), No. 2, 2024, pp. e23027.
DOI Link
2402
amide proton transfer-weighted, compressed sensing, glioma,
radiomics, sensitivity encoding
BibRef
Liu, X.Y.[Xiang-Yuan],
Wu, Z.[Zhongke],
Wang, X.[Xingce],
Liu, Q.S.[Quan-Sheng],
Pozo, J.M.[Jose M.],
Frangi, A.F.[Alejandro F.],
Joint magnetic resonance imaging artifacts and noise reduction on
discrete shape space of images,
PR(153), 2024, pp. 110495.
Elsevier DOI
2405
Artifact and noise, Discrete shape space of images,
Riemannian manifold, PROD detector
BibRef
Jiang, B.[Bowen],
Yue, T.[Tao],
Hu, X.M.[Xue-Mei],
An improved attentive residue multi-dilated network for thermal noise
removal in magnetic resonance images,
IVC(150), 2024, pp. 105213.
Elsevier DOI
2409
Adaptive filtering, Discrete cosine transform (DCT),
Image denoising, Magnetic resonance imaging (MRI), Rician noise
BibRef
Hod, G.[Gali],
Green, M.[Michael],
Waserman, M.[Mark],
Konen, E.[Eli],
Shrot, S.[Shai],
Nelkenbaum, I.[Ilya],
Kiryati, N.[Nahum],
Mayer, A.[Arnaldo],
Complementary Phase Encoding for Pair-wise Neural Deblurring of
Accelerated Brain MRI,
MCV22(268-280).
Springer DOI
2304
BibRef
Upadhyay, U.[Uddeshya],
Sudarshan, V.P.[Viswanath P.],
Awate, S.P.[Suyash P.],
Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image
Enhancement,
CVAMD21(3248-3257)
IEEE DOI
2112
Adaptation models, Uncertainty, Magnetic resonance imaging,
Perturbation methods, Generative adversarial networks
BibRef
Liang, S.J.[Shi-Jun],
Iskender, B.[Berk],
Wen, B.[Bihan],
Ravishankar, S.[Saiprasad],
Labmat: Learned Feature-Domain Block Matching for Image Restoration,
ICIP21(1689-1693)
IEEE DOI
2201
Wavelet transforms, Wavelet domain, Limiting,
Magnetic resonance imaging, Noise reduction, Tomography, Transform learning
BibRef
Armanious, K.,
Kumar, V.,
Abdulatif, S.,
Hepp, T.,
Gatidis, S.,
Yang, B.,
ipA-MedGAN: Inpainting of Arbitrary Regions in Medical Imaging,
ICIP20(3005-3009)
IEEE DOI
2011
Feature extraction, Medical diagnostic imaging, Logic gates,
Task analysis, Magnetic resonance imaging, image translation
BibRef
Thurnhofer-Hemsi, K.,
López-Rubio, E.,
Roé-Vellvé, N.,
Deka, L.,
Super-Resolution of 3D MRI Corrupted by Heavy Noise With the Median
Filter Transform,
ICIP20(3015-3019)
IEEE DOI
2011
Spatial resolution,
Magnetic resonance imaging, Noise reduction, Interpolation,
single image super-resolution
BibRef
Liu, J.[Jia],
Chen, F.[Fang],
Wang, X.Y.[Xian-Yu],
Liao, H.[Hongen],
An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection
Direction,
MBIA19(12-20).
Springer DOI
1912
BibRef
Bazgir, O.,
Mitra, S.,
Nutter, B.,
Walden, E.,
Fully Automatic Baseline Correction in Magnetic Resonance
Spectroscopy,
Southwest18(97-100)
IEEE DOI
1809
Phantoms, In vivo, Magnetic resonance, Atmospheric modeling,
Lipidomics, Tuning, Spectroscopy,
Neurodegenerative disorders
BibRef
Teixeira, J.F.[João F.],
Oliveira, H.P.[Hélder P.],
Spacial Aliasing Artefact Detection on T1-Weighted MRI Images,
IbPRIA17(462-470).
Springer DOI
1706
BibRef
Martín, A.[Adrián],
Schiavi, E.[Emanuele],
Noise Modelling in Parallel Magnetic Resonance Imaging:
A Variational Approach,
ICIAR14(I: 121-128).
Springer DOI
1410
BibRef
Vanathe, V.,
Boopathy, S.,
Manikandan, M.A.,
MR image denoising and enhancing using multiresolution image
decomposition technique,
ICSIPR13(29-33).
IEEE DOI
1304
BibRef
Yepes, F.[Fernando],
Lao, Y.[Yi],
Fillard, P.[Pierre],
Justicia, C.[Carles],
Planas, A.[Anna],
Nelson, M.D.[Marvin D.],
Soria, G.[Guadalupe],
Lepore, N.[Natasha],
Improving image quality in small animal diffusion tensor imaging at 7T,
ICIP12(985-988).
IEEE DOI
1302
BibRef
Getreuer, P.[Pascal],
Tong, M.[Melissa],
Vese, L.A.[Luminita A.],
A Variational Model for the Restoration of MR Images Corrupted by Blur
and Rician Noise,
ISVC11(I: 686-698).
Springer DOI
1109
BibRef
Luisier, F.[Florian],
Wolfe, P.J.[Patrick J.],
Chi-square unbiased risk estimate for denoising magnitude MR images,
ICIP11(1561-1564).
IEEE DOI
1201
BibRef
Mohan, J,
Krishnaveni, V,
Guo, Y.H.[Yan-Hui],
A Neutrosophic approach of MRI denoising,
ICIIP11(1-6).
IEEE DOI
1112
BibRef
Soto, M.E.[Miguel E.],
Pezoa, J.E.[Jorge E.],
Torres, S.N.[Sergio N.],
Thermal Noise Estimation and Removal in MRI:
A Noise Cancellation Approach,
CIARP11(47-54).
Springer DOI
1111
BibRef
Wei, S.M.[Si-Ming],
Hua, J.[Jing],
Bu, J.J.[Jia-Jun],
Chen, C.[Chun],
Yu, Y.Z.[Yi-Zhou],
Bayesian regularization of diffusion tensor images using hierarchical
MCMC and loopy belief propagation,
ICIP10(65-68).
IEEE DOI
1009
BibRef
Rajan, J.,
Jeurissen, B.,
Sijbers, J.,
Kannan, K.,
Denoising Magnetic Resonance Images Using Fourth Order Complex
Diffusion,
IMVIP09(123-127).
IEEE DOI
0909
BibRef
Tan, L.[Lina],
Shi, L.W.[Liang-Wu],
Multiwavelet-Based Estimation for Improving Magnetic Resonance Images,
CISP09(1-5).
IEEE DOI
0910
BibRef
Ardizzone, E.[Edoardo],
Pirrone, R.[Roberto],
La Bua, S.[Salvatore],
Gambino, O.[Orazio],
Volumetric Bias Correction,
MIRAGE07(525-533).
Springer DOI
0703
Bias correction in MRI data.
BibRef
Belaroussi, B.,
Benoit-Cattin, H.,
Odet, C.,
CASTI: Correction of Susceptibility Artifact in MR Images using MRI
Simulation,
ICIP06(897-900).
IEEE DOI
0610
BibRef
Thacker, N.A.,
Pokric, M.,
Williamson, D.C.,
Noise Filtering and Testing Illustrated Using a Multi-Dimensional
Partial Volume Model of MR Data,
BMVC04(xx-yy).
HTML Version.
0508
BibRef
Blezek, D.J.[Daniel J.],
Dixon, W.T.[W. Thomas],
Dhawale, P.J.[Paritosh J.],
Single Image Phase-Based MRI Fat Suppression Expectation Maximization
Algorithm,
CVPR05(II: 540-546).
IEEE DOI
0507
BibRef
Gispert, J.D.,
Reig, S.,
Pascau, J.,
Lazaro, R.M.,
Vaquero, J.J.,
Desco, M.,
Inhomogeneity correction of magnetic resonance images by minimization
of intensity overlapping,
ICIP03(II: 847-850).
IEEE DOI
0312
BibRef
Aggarwal, N.,
Bresler, Y.,
Optimal sampling in parallel magnetic resonance imaging,
ICIP03(II: 839-842).
IEEE DOI
0312
BibRef
Fadili, M.,
Bullmore, E.,
Brett, M.,
Wavelet Methods for Characterising Mono- and Poly-fractal Noise
Structures in Shortish Time Series: an Application to Functional MRI,
ICIP01(II: 225-228).
IEEE DOI
0108
BibRef
Jiang, T.,
Kruggel, F.,
3D MR Image Restoration by Combining Local Genetic Algorithm with
Adaptive Pre-conditioning,
ICPR00(Vol III: 298-301).
IEEE DOI
IEEE DOI
0009
BibRef
Osman, N.F.,
Prince, J.L.,
On the Design of the Bandpass Filters in Harmonic Phase MRI,
ICIP00(Vol I: 625-628).
IEEE DOI
0008
BibRef
Jammal, G.[Ghada],
Bijaoui, A.[Albert],
Denoising and Deconvolution in Nuclear Medicine,
ICIP99(III:896-900).
IEEE DOI
BibRef
9900
Garza-Jinich, M.,
Yanez, O.,
Medina, V.,
Meer, P.,
Automatic correction of bias field in magnetic resonance images,
CIAP99(752-756).
IEEE DOI
9909
BibRef
Bajla, I.,
Marušiak, M.,
Šrámek, M.,
Anisotropic filtering of MRI data based upon image gradient histogram,
CAIP93(90-97).
Springer DOI
9309
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
MRI, Surveys, Overviews, Evaluations .