Advance image processing in magnetic resonance imaging

Advanced Image Processing in Magnetic Resonance Imaging......Page 3
Preface......Page 5
Contributors......Page 6
Contents......Page 9
Part I: Signal and Image Generation and Reconstruction......Page 12
CONTENTS......Page 13
1.1 INTRODUCTION......Page 14
1.2 NUCLEAR SPIN......Page 16
1.3 NUCLEI IN A MAGNETIC FIELD......Page 17
1.3.1 NOTES ON LARMOR FREQUENCY: CHANGES DUE TO DISHOMOGENEITIES......Page 19
1.3.2 BULK MAGNETIZATION......Page 20
1.4 RF EXCITATION FOR THE RESONANCE PHENOMENON GENERATION......Page 21
1.5.1 FREE INDUCTION DECAY AND THE FOURIER TRANSFORM......Page 24
1.6.1.2 The Recovery of Longitudinal Magnetization: T1......Page 26
1.6.2 PROTON DENSITY......Page 27
1.7 MULTIPLE RF PULSES......Page 28
1.7.2 INVERSION RECOVERY......Page 29
1.7.3 SPIN ECHO......Page 30
1.8 MAGNETIC FIELD GRADIENTS......Page 33
1.9.1 SLICE SELECTION......Page 34
1.9.2 FREQUENCY ENCODING......Page 36
1.9.4 PHASE HISTORY OF MAGNETIZATION VECTORS DURING PHASE ENCODING......Page 38
1.9.5 TIMING DIAGRAM OF AN IMAGING SEQUENCE......Page 39
1.10 ACQUIRING MR SIGNALS IN THE K-SPACE......Page 40
1.11 IMAGING METHODS......Page 43
REFERENCES......Page 46
CONTENTS......Page 48
2.2 FOURIER RECONSTRUCTION......Page 49
2.3.1 NONPARAMETRIC METHODS......Page 52
2.3.2 PARAMETRIC METHODS......Page 54
Example 2.1: Partial Fourier Reconstruction......Page 55
Example 2.2: Data-Sharing Dynamic Imaging......Page 56
2.4.1 BASIC RECONSTRUCTION METHODS......Page 57
2.4.2.1 Construction of…......Page 59
2.4.2.2 Selection of lambda......Page 60
2.4.2.3 Sensitivity Analysis......Page 61
2.4.3 APPLICATION EXAMPLE......Page 62
2.5 CONCLUSION......Page 63
REFERENCES......Page 64
3.1 INTRODUCTION......Page 66
3.2 HISTORY OF PARALLEL MRI......Page 67
3.3 FORMULATION OF THE PROBLEM......Page 70
3.3.1 FOURIER ENCODING......Page 71
3.3.2 SAMPLING AT THE NYQUIST RATE AND EQUATION INDEPENDENCE......Page 72
3.3.3.1.2 Dynamic Self-Calibrated Estimate......Page 73
3.3.3.3.1 SMASH......Page 74
3.3.3.3.3 GRAPPA......Page 77
3.3.3.4.1 SENSE......Page 79
3.3.3.4.2 SPACE RIP......Page 80
3.4.1 EXAMPLE 1: UNIFORM SUBSAMPLING......Page 83
3.4.2 EXAMPLE 2: VARIABLE SUBSAMPLING......Page 85
3.4.3 EXAMPLE 3: IN VIVO APPLICATIONS......Page 88
REFERENCES......Page 89
Part II: SNR Improvement and Inhomogeneities Correction......Page 91
CONTENTS......Page 92
4.1 INTRODUCTION......Page 93
4.2.1 GAUSSIAN PDF......Page 94
4.2.2 RICIAN PDF......Page 95
4.2.2.1 Asymptotic Approximation of the Rician Distribution......Page 96
4.2.2.2 Moments of the Rician PDF......Page 97
4.2.2.4 Generalized Rician PDF......Page 98
4.2.2.5 Moments of the Generalized Rician PDF......Page 99
4.2.2.6 PDF of Squared Magnitude Data......Page 100
4.2.3 PDF OF PHASE DATA......Page 101
4.3.2 PRECISION......Page 103
4.3.5 CRLB......Page 104
4.3.6 ML ESTIMATION......Page 105
4.4.1 INTRODUCTION......Page 106
4.4.2.1 Region of Constant Amplitude and Phase......Page 108
4.4.2.1.2 ML Estimation......Page 109
4.4.2.2 Region of Constant Amplitude and Different Phases......Page 110
4.4.2.2.2 ML Estimation......Page 111
4.4.3 SIGNAL AMPLITUDE ESTIMATION FROM MAGNITUDE DATA......Page 112
4.4.3.1.2 Conventional Estimation......Page 113
4.4.3.1.3 Discussion......Page 114
4.4.3.1.4 ML Estimation......Page 116
4.4.3.1.5 Discussion......Page 117
4.4.3.2.1 CRLB......Page 120
4.4.4 DISCUSSION......Page 121
4.4.4.1 CRLB......Page 122
4.4.4.2 MSE......Page 123
4.4.5.1.1 CRLB......Page 125
4.4.5.1.3 Modified RMS Estimator......Page 126
4.4.5.2 Experiments and Discussion......Page 129
4.5.1 INTRODUCTION......Page 130
4.5.2.1.1 CRLB......Page 131
4.5.2.2 Region of Constant Amplitude and Different Phases......Page 132
4.5.2.2.2 ML Estimation......Page 133
4.5.2.3.3 MSE......Page 134
4.5.3.1.2 CRLB (Standard Deviation)......Page 135
4.5.3.1.3 ML Estimation......Page 136
4.5.3.1.4 Conventional Estimation......Page 137
4.5.3.3 Double-Acquisition Method......Page 138
4.5.4.2 MSE......Page 140
4.7.1.1 Theorem......Page 143
4.7.2 GENERAL THEOREM......Page 144
4.7.3.2 Example......Page 145
SYMBOLS......Page 146
REFERENCES......Page 147
5.1 INTRODUCTION......Page 151
5.2 EARLY SOLUTIONS......Page 154
5.3 COMBINED SEGMENTATION AND INHOMOGENEITY CORRECTION METHODS......Page 155
5.4.1 PARAMETRIC BIAS CORRECTION......Page 166
5.4.2 INFORMATION MINIMIZATION AND N3......Page 169
5.5 DISCUSSION AND CONCLUSION......Page 170
REFERENCES......Page 171
6.1 INTRODUCTION......Page 175
6.2 THE MR IMAGE MODEL......Page 177
6.3 WAVELET-BASED FILTERING......Page 178
6.4 ADAPTIVE TEMPLATE FILTERING......Page 180
6.5 ANISOTROPIC DIFFUSION FILTERING......Page 183
6.6 APPLICATION OF ANISOTROPIC DIFFUSION FILTERING......Page 185
REFERENCES......Page 189
Part III: Image Processing and Quantitative Analysis......Page 192
7.1 INTRODUCTION......Page 193
7.2 THE REGISTRATION PROBLEM......Page 196
7.3 SIMILARITY METRICS......Page 197
7.3.1 MUTUAL INFORMATION......Page 200
7.3.2 PHANTOM EXPERIMENTS......Page 201
7.4 THE INTERPOLATION EFFECT IN THE REGISTRATION PROBLEM......Page 203
7.5 OPTIMIZATION TECHNIQUES IN IMAGE REGISTRATION......Page 205
7.5.1 NELDER–MEAD SIMPLEX ALGORITHM......Page 206
7.5.2 GENETIC ALGORITHMS......Page 207
7.6 REGISTRATION OF MULTIPLE DATA SETS......Page 209
7.7 BRAIN IMAGES REGISTRATION......Page 215
7.7.1 FMRI IMAGES REGISTRATION......Page 216
7.7.3 FMRI REGISTRATION EXPERIMENT......Page 217
7.8 CARDIAC IMAGES REGISTRATION......Page 219
REFERENCES......Page 222
CONTENTS......Page 226
8.1 INTRODUCTION......Page 227
8.2 SOURCE LOCALIZATION IN EEG AND MEG......Page 228
8.2.1 ASSUMPTIONS UNDERLYING INTEGRATION OF EEG AND MEG......Page 229
8.2.2 FORWARD MODELING......Page 231
8.2.3.1 Equivalent Current Dipole Models......Page 232
8.2.3.2 Linear Inverse Methods: Distributed ECD......Page 233
8.2.3.3 Beamforming......Page 236
8.3.1 MEASURING EEG DURING MRI: CHALLENGES AND APPROACHES......Page 238
8.3.2 EXPERIMENTAL DESIGN LIMITATIONS......Page 240
8.4.1 USING ANATOMICAL MRI......Page 241
8.4.1.1 Registration of EEG and MEG to MRI......Page 242
8.4.1.2 Segmentation and Tessellation......Page 243
8.4.2 FORWARD MODELING OF BOLD SIGNAL......Page 244
8.4.2.1 Convolutional Model of BOLD Signal......Page 246
8.4.2.2 Neurophysiologic Constraints......Page 247
8.4.3.1 Correlative Analysis of EEG and MEG with fMRI......Page 249
8.4.3.2 Decomposition Techniques......Page 250
8.4.3.4 Linear Inverse Methods......Page 251
8.4.3.6 Bayesian Inference......Page 253
8.5 CONSIDERATIONS AND FUTURE DIRECTIONS......Page 256
REFERENCES......Page 257
CONTENTS......Page 269
ABSTRACT......Page 270
9.1 INTRODUCTION......Page 271
9.2.1 ANGIOCARDIOGRAPHY......Page 273
9.2.4 CARDIAC COMPUTED TOMOGRAPHY......Page 286
9.2.5 MAGNETIC RESONANCE IMAGING......Page 287
9.3.1 GLOBAL FUNCTIONAL ANALYSIS......Page 289
9.3.2.2 Wall Thickening......Page 292
9.3.2.3 Strain Analysis......Page 293
9.4 OVERVIEW OF MODELING TECHNIQUES......Page 294
9.4.1.1.1 Global Approaches......Page 295
9.4.1.1.2 Hierarchical Approaches......Page 296
9.4.1.1.3 Local Approaches......Page 297
9.4.1.2.1 Physics-Based Models......Page 298
9.4.1.2.3 Polygonal Models......Page 300
9.4.1.2.4 Statistical Shape and Appearance Models......Page 301
9.4.1.3 Implicitly Defined Deformable Models......Page 303
9.4.2 VOLUMETRIC MODELS......Page 304
9.4.3.1.1 Continuous Models......Page 306
9.4.3.1.2 Discrete Models......Page 307
9.4.3.2.1 Continuous Models......Page 308
9.4.3.2.2 Discrete Models......Page 315
9.5.1 VALIDATION......Page 316
9.5.2.1 Model Complexity or Flexibility......Page 317
9.5.2.2 Robustness and Effective Automation......Page 319
9.6 CONCLUSIONS AND SUGGESTIONS FOR FUTURE RESEARCH......Page 320
NOMENCLATURE......Page 323
Shape Index and Shape Spectrum......Page 325
LOCAL STRETCHING......Page 326
Deformable Superquadric and Related Models......Page 327
Modal Analysis: Deformation Spectrum......Page 328
MR TAG LOCALIZATION TECHNIQUES......Page 329
REFERENCES......Page 330
10.1 INTRODUCTION......Page 348
10.2.1 SELECTIVE TAGGING......Page 349
10.2.2 SPATIAL MODULATION OF MAGNETIZATION......Page 350
10.2.3 COMPLEMENTARY SPAMM......Page 352
10.3.1 STRIPE TRACKING......Page 354
10.3.3 NONHOMOGENEOUS STRAIN......Page 355
10.3.4 RECONSTRUCTION OF 3-D KINEMATICS......Page 356
10.4.1 THEORY......Page 358
10.4.2 KINEMATICS......Page 360
10.5 PHASE-CONTRAST VELOCITY......Page 361
10.6.1 THEORY......Page 363
10.6.2 CSPAMM DENSE (CINE-DENSE)......Page 364
10.7 DIFFUSION......Page 365
10.9 CONCLUSIONS......Page 367
REFERENCES......Page 368
Part IV: Spectroscopy, Diffusion, Elasticity: From Modeling to Parametric Image Generation......Page 371
11.1 INTRODUCTION......Page 372
11.2 SVS......Page 373
11.2.1 PRESS AND STEAM......Page 374
11.2.2 ARTIFACTS IN SVS......Page 380
11.2.3 WATER SUPPRESSION......Page 383
11.2.4 COUPLING EFFECTS IN SVS......Page 387
11.3.1 BASIC PRINCIPLES......Page 389
11.3.2 AVOIDING UNDESIRED EXCITATIONS......Page 392
11.3.3 RECONSTRUCTION OF CSI DATA......Page 395
11.3.4 K-SPACE WEIGHTING TECHNIQUES......Page 400
11.3.5 CSI PREPROCESSING......Page 403
11.3.6 DISPLAY OF THE CSI DATA......Page 404
11.3.7 COMPARISON OF SVS AND CSI TECHNIQUES......Page 407
11.4 DIFFERENCES IN SEQUENCES FOR MEASUREMENTS WITH NONPROTON NUCLEI......Page 408
REFERENCES......Page 409
12.1 INTRODUCTION......Page 413
12.2 EXTRACTING INFORMATION FOR THE FID SIGNAL......Page 415
12.3.2 WINDOWING......Page 418
12.3.3 REMOVAL OF UNDESIRED RESONANCE......Page 419
12.4 FREQUENCY-DOMAIN METHODS......Page 420
12.5 TIME-DOMAIN METHODS......Page 421
REFERENCES......Page 425
13.1 INTRODUCTION......Page 429
13.2 DIFFUSION AND DIFFUSION TENSOR CALCULATION......Page 431
13.3 ANISOTROPY AND MACROSTRUCTURAL MEASURES......Page 432
13.3.1 GEOMETRICAL MEASURES OF DIFFUSION......Page 433
13.3.2 MACROSTRUCTURAL TENSOR AND DIFFUSIVE MEASURES......Page 436
13.4 VISUALIZATION OF DIFFUSION TENSORS......Page 440
13.5 CONNECTIVITY ANALYSIS......Page 442
13.6 METHOD ONE: DIFFUSION-BASED CONNECTIVITY......Page 443
13.6.1 EXPERIMENTS......Page 444
13.7 METHOD TWO: DISTANCE-BASED CONNECTIVITY......Page 445
13.7.2 EXPERIMENTS......Page 447
13.8 CONCLUSION......Page 448
REFERENCES......Page 450
CONTENTS......Page 452
14.1 INTRODUCTION......Page 453
14.3 MR ELASTICITY IMAGING TECHNIQUES......Page 454
14.4 MRE......Page 455
14.5 DATA PROCESSING......Page 458
14.5.1 EQUATIONS OF MOTION......Page 459
14.5.2 SHEAR MODULUS AND MECHANICAL FREQUENCY......Page 460
14.5.4 LOCAL FREQUENCY ESTIMATION (LFE)......Page 461
14.5.5 DIRECT INVERSION......Page 462
14.5.8 REMOVING THE LOCAL HOMOGENEITY ASSUMPTION......Page 463
14.5.10 ANISOTROPIC INVERSIONS......Page 464
14.5.12 SIGNAL-TO-NOISE CONSIDERATIONS......Page 465
14.6.1 PHANTOM OBJECT......Page 466
14.6.2 ANIMAL TISSUES......Page 468
14.6.3 BREAST......Page 469
14.6.5 MUSCLE......Page 471
14.6.6 ULTRASOUND WAVE FIELD VISUALIZATION......Page 472
14.6.7 CHARACTERIZATION OF THERMALLY ABLATED TISSUE......Page 473
ACKNOWLEDGMENTS......Page 474
REFERENCES......Page 475
Part V: BOLD Contrast MR Imaging and fMRI Signal Analysis......Page 479
15.1 INTRODUCTION......Page 480
15.2.1 SLICE TIMING CORRECTION......Page 482
15.2.2 MOTION CORRECTION......Page 483
15.2.3 SPATIAL AND TEMPORAL FILTERING......Page 484
15.3 STATISTICAL LOCALIZATION OF BRAIN ACTIVATION......Page 487
15.3.1 THE GLM......Page 488
15.3.1.1 Overall Effects (R2 Maps, F Maps)......Page 490
15.3.1.3 Specific Effects, Contrasts (t Maps)......Page 492
15.4 SELECTION OF SIGNIFICANCE THRESHOLDS IN FMRI STATISTICAL MAPS......Page 493
15.6.1 COREGISTRATION OF FUNCTIONAL AND ANATOMICAL DATA SETS......Page 495
15.6.2 SPATIAL NORMALIZATION......Page 496
15.7 SEGMENTATION, SURFACE RECONSTRUCTION, AND MORPHING......Page 497
REFERENCES......Page 499
CONTENTS......Page 503
16.2 MULTIVARIATE APPROACHES......Page 504
16.3 DATA CLUSTERING APPROACHES......Page 506
16.3.1 SIMILARITY......Page 507
16.3.2.1 Hierarchical Methods......Page 508
16.3.2.2 Hard Partitioning Methods......Page 510
16.3.2.3 Fuzzy Clustering......Page 511
16.3.2.4 Artificial Neural Networks......Page 513
16.4 PCA......Page 514
16.4.1 SPATIAL AND TEMPORAL PCA......Page 515
16.4.2 INTERPRETATION OF THE PCA DECOMPOSITION......Page 518
16.5 ICA......Page 520
16.5.1 SPATIAL AND TEMPORAL ICA......Page 521
16.5.2.1 Historical Background......Page 522
16.5.2.2 Nonlinear Decorrelation......Page 523
16.5.2.2.1 Whitening as a Preprocessing Step......Page 524
16.5.2.3 Information Maximization and Maximum Likelihood Approaches......Page 525
16.5.2.4 Non-Gaussianity and Negentropy......Page 527
16.5.3 PREPROCESSING......Page 528
16.5.4 MODEL VALIDATION......Page 530
16.5.5.2 Task-Related Activations......Page 531
REFERENCES......Page 533
17.1 INTRODUCTION......Page 539
17.2 SPATIAL TRANSFORMATIONS......Page 541
17.2.2 ADJUSTING FOR MOVEMENT-RELATED EFFECTS IN FMRI......Page 542
17.2.4 COREGISTRATION OF FUNCTIONAL AND ANATOMICAL DATA......Page 543
17.2.5 SPATIAL SMOOTHING......Page 544
17.3.1 DESIGN MATRIX......Page 545
17.3.2 CONTRASTS......Page 546
17.3.3 TEMPORAL BASIS FUNCTIONS......Page 547
17.4 STATISTICAL PARAMETRIC MAPPING......Page 549
17.4.1 RANDOM FIELD THEORY......Page 550
17.5 POSTERIOR PROBABILITY MAPPING......Page 551
17.5.1 EMPIRICAL EXAMPLE......Page 552
17.6 DYNAMIC CAUSAL MODELING......Page 554
17.6.1 EMPIRICAL EXAMPLE......Page 555
REFERENCES......Page 560
18.1 INTRODUCTION......Page 562
18.2.2 FEATURES OF FMRI DATA......Page 563
18.2.4 OVERVIEW......Page 564
18.3 STATISTICAL LEARNING THEORY......Page 565
18.4.2 TEMPORAL MODELING......Page 568
18.4.3 MULTIRESOLUTION SIGNAL ANALYSIS......Page 570
18.4.4 MERGING MODEL-DRIVEN WITH DATA-DRIVEN METHODS......Page 572
18.4.5 GENERALIZATION TO MULTISESSION STUDIES......Page 573
18.4.6 TESTING ON REAL FMRI DATA......Page 575
18.5 CONCLUSIONS AND DISCUSSIONS......Page 578
REFERENCES......Page 579
CONTENTS......Page 583
19.2.1 TRANSPORT FUNCTION......Page 584
19.2.3 CEREBRAL BLOOD VOLUME......Page 585
19.2.5 CEREBRAL BLOOD FLOW......Page 587
19.3.1 FROM DSC-MRI SIGNAL TO TRACER CONCENTRATION......Page 589
19.3.2 ARTERIAL INPUT FUNCTION......Page 590
19.3.3 DECONVOLUTION......Page 592
19.3.4 ABSOLUTE QUANTIFICATION ISSUES......Page 595
REFERENCES......Page 597