Contributors ................................................. xiii
Chapter 1
T-SURFACES FRAMEWORK FOR OFFSET GENERATION AND
SEMIAUTOMATIC 3D SEGMENTATION ................................... 1
Gilson A. Giraldi, Rodrigo L.S. Silva, Paulo S.S.
Rodrigues, Walter Jiménez, Edilberto Strauss, Antonio
A.F. Oliveira, and Jasjit S. Suri
1. Introduction ................................................ 2
2. Background and Previous Works ............................... 4
3. Isosurface Extraction Methods .............................. 10
4. T-Surfaces and Isosurface Methods .......................... 12
5. Reconstruction Method and Offset Generation ................ 13
6. Experimental Results ....................................... 16
7. Discussion and Perspectives ................................ 22
8. Conclusions and Future Work ................................ 26
9. Acknowledgments ............................................ 26
10. References ................................................. 26
Chapter 2
PARAMETRIC CONTOUR MODEL IN MEDICAL
IMAGE SEGMENTATION ............................................. 31
Bipul Das and Swapna Banerjee
1. Introduction ............................................... 32
2. Active Contour Model: Theory ............................... 35
3. Active Contour Evolution ................................... 40
4. A-Priori Information ....................................... 53
5. Topological Snake .......................................... 62
6. Discussion and Conclusions ................................. 64
7. References ................................................. 71
Chapter 3
DEFORMABLE MODELS AND THEIR APPLICATION IN
SEGMENTATION OF IMAGED PATHOLOGY SPECIMENS ..................... 75
Lin Yang and David J. Foran
1. Introduction ............................................... 75
2. Mathematical Background of Deformable Models ............... 79
3. Parametric Deformable Models ............................... 82
4. Geodesic or Level Set-Based Deformable Models .............. 87
5. Concluding Remarks ......................................... 91
6. Acknowledgments ............................................ 93
7. References ................................................. 93
Chapter 4
IMAGE SEGMENTATION USING THE LEVEL SET METHOD .................. 95
Yingge Qu, Pheng Ann Heng, and Tien-Tsin Wong
1. Introduction ............................................... 96
2. Related Work ............................................... 97
3. Level Set Methods and Image Segmentation .................. 100
4. Augmenting the Speed Function ............................. 108
5. Semiautomatic Segmentation and Tracking of Serial
Medical Images ............................................ 115
6. Conclusion ................................................ 118
7. Acknowledgments ........................................... 120
8. References ................................................ 120
Chapter 5
PARALLEL CO-VOLUME SUBJECTIVE SURFACE METHOD
FOR 3D MEDICAL IMAGE SEGMENTATION ............................. 123
Karol Mikula and Alessandro Sarti
1. Introduction .............................................. 123
2. Mathematical Models in Image Segmentation ................. 124
3. Semi-Implicit 3D Co-Volume Scheme ......................... 130
4. Building up the Parallel Algorithm ........................ 139
5. Discussion of Computational Results ....................... 149
6. Acknowledgments ........................................... 157
7. References ................................................ 157
Chapter 6
VOLUMETRIC SEGMENTATION USING SHAPE MODELS IN THE
LEVEL SET FRAMEWORK ........................................... 161
Fuxing Yang, Milan Sonka, and Jasjit S. Suri
1. Introduction .............................................. 161
2. Brief Mathematical Formulation of Level Sets .............. 163
3. Basic Application of Level Set Methods .................... 166
4. Active Contours in the Level Set Framework ................ 174
5. Image Segmentation Using Shape Prior ...................... 186
6. Conclusions ............................................... 203
7. Acknowledgments ........................................... 204
8. References ................................................ 204
Chapter 7
MEDICAL IMAGE SEGMENTATION BASED ON DEFORMABLE
MODELS AND ITS APPLICATIONS ................................... 209
Yonggang Wang, Yun Zhu, and Qiang Guo
1. Medical Image Segmentation ................................ 209
2. Deformable Models ......................................... 217
3. Tongue Body Extraction Based on a Color GVF Snake ......... 222
4. Tongue Segmentation Based on a Color GVF Snake ............ 227
5. Cerebral Cortex MR Image Segmentation ..................... 231
6. Prior-Based Cardiac Valve Segmentation Using a
Geodesic Snake ............................................ 248
7. References ................................................ 256
Chapter 8
BREAST STRAIN IMAGING:
A CAD FRAMEWORK ............................................... 261
Ruey-Feng Chang, Chii-Jen Chen, Chia-Ling Tsai,
Wei-Liang Chen, and Jasjit S. Suri
1. Introduction .............................................. 262
2. General Ultrasound Image Analysis Achitecture ............. 263
3. Ultrasound Data Acquisition System ........................ 263
4. Theory of Front Evolution for Boundary Estimation of
Lesion .................................................... 266
5. 2D Continuous Strain Mode System .......................... 270
6. Conclusion ................................................ 286
7. References ................................................ 286
Chapter 9
ALTERNATE SPACES FOR MODEL DEFORMATION: APPLICATION
OF STOP AND GO ACTIVE MODELS TO MEDICAL IMAGES ................ 289
Oriol Pujol and Petia Radeva
1. Introduction .............................................. 289
2. Analysis of Current Geometric Snakes ...................... 292
3. Stop and Go Formulation ................................... 294
4. Deformable Models in the Classification Pipeline .......... 297
5. Stop and Go Snakes Design ................................. 312
6. Experimental Results ...................................... 313
7. Conclusions ............................................... 321
8. Acknowledgments ........................................... 322
9. References ................................................ 322
Chapter 10
DEFORMABLE MODEL-BASED SEGMENTATION OF THE
PROSTATE FROM ULTRASOUND IMAGES ............................... 325
Aaron Fenster, Hanif Ladak, and Mingyue Ding
1. Introduction .............................................. 325
2. Prostate Boundary Segmentation from 2D TRUS Images ........ 327
3. Testing and Optimization Using Virtual Operators .......... 339
4. 3D Segmentation ........................................... 346
5. Summary and Discussion .................................... 364
6. References ................................................ 367
Chapter 11
SEGMENTATION OF BRAIN MR IMAGES USING J-DIVERGENCE-
BASED ACTIVE CONTOUR MODELS ................................... 371
Wanlin Zhu, Tianzi Jiang, and Xiaobo Li
1. Introduction .............................................. 371
2. Methods ................................................... 374
3. Experimental Results ...................................... 382
4. Conclusions and Future Research ........................... 386
5. Acknowledgments ........................................... 387
Al Appendix: Derivation of Level Set Evolution Equation ...... 387
6. References ................................................ 390
Chapter 12
MORPHOMETRIC ANALYSIS OF NORMAL AND PATHOLOGIC
BRAIN STRUCTURE VIA HIGH-DIMENSIONAL
SHAPE TRANSFORMATIONS ......................................... 393
Ashraf Mohamed and Christos Davatzikos
1. Introduction .............................................. 393
2. Shape Transformations and Deformable Registration of
Brain Images .............................................. 397
3. Voxel-Based Morphometric Analysis ......................... 402
4. Deformable Registration of Brain Atlases to Brain Tumor
Images .................................................... 412
5. Conclusion ................................................ 439
6. Acknowledgments ........................................... 440
7. References ................................................ 440
Chapter 13
EFFICIENT KERNEL DENSITY ESTIMATION OF SHAPE AND
INTENSITY PRIORS FOR LEVEL SET SEGMENTATION ................... 447
Daniel Cremers and Mikael Rousson
1. Introduction .............................................. 447
2. Level Set Segmentation as Bayesian Inference .............. 449
3. Efficient Nonparametric Statistical Shape Model ........... 450
4. Energy Formulation add Minimization ....................... 452
5. Experimental Results and Validation ....................... 453
6. Conclusion ................................................ 459
7. Acknowledgments ........................................... 459
8. Notes ..................................................... 460
9. References ................................................ 460
Chapter 14
VOLUMETRIC MRI ANALYSIS OF DYSLEXIC SUBJECTS
USING A LEVEL SET FRAMEWORK ................................... 461
H. Abd El Munim, R. Fahmi, N. Youssry El-Zehiry,
A.A. Farag, and M. Casanova
1. Introduction .............................................. 462
2. The Neuroanatonomy Background ............................. 463
3. Problem Statement, Dataset Description and Proposed
Approach .................................................. 466
4. Proposed Approach ......................................... 469
5. Conclusion ................................................ 488
6. Appendix: Pseudo Code for the Segmentation Algorithm ...... 488
7. References ................................................ 490
Chapter 15
ANALYSIS OF 4-D CARDIAC MR DATA WITH NURBS DEFORMABLE
MODELS: TEMPORAL FITTING STRATEGY AND NONRIGID
REGISTRATION .................................................. 493
Nicholas J. Tustison and Amir A. Amini
1. Introduction .............................................. 494
2. NURBS Model ............................................... 496
3. Mathematical Preliminaries ................................ 500
4. Model Fitting and Nonrigid Registration ................... 504
5. Lagrangian and Eulerian Strain Measurements form an
NURBS Model ............................................... 513
6. Results ................................................... 516
7. Conclusions ............................................... 529
8. References ................................................ 532
Chapter 16
ROBUST NEUROIMAGING-BASED CLASSIFICATION TECHNIQUES
OF AUTISTIC VS. TYPICALLY DEVELOPING BRAIN .................... 535
Rachid Fahmi, Ayman El-Baz, Hossam Abd El-Munim,
Alaa E. Abdel-Hakim, Aly A. Farag and Manuel F. Casanova
1. Introduction .............................................. 536
2. Subjects and Image Acquision .............................. 541
3. Image Processing and Analysis ............................. 543
4. Proposed Classification Approaches ........................ 555
5. Discussion ................................................ 562
6. References ................................................ 563
Index ......................................................... 567
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