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233, No. 1, January 2004, pp. 14–21.
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Base Cancers—A Feasibility Study,” Proc. 34th Int. MATADOR Conf., Manchester, U.K.,
July 7–9, 2004.
[34] Chauhan, S., “FUSBOT—An Ultrasound Guided Robot for Focal Ultrasound Surgery,”
Proc. Int. Symp. Therapeutic Ultrasound, Kyoto, Japan, September 18–20, 2004.
[35] Häcker, A., et al., “Multiple HIFU-Probes for Kidney Tissue Ablation,” Journal of
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414 Modalities and Devices for Thermal Ablation
About the Editors
Jasjit Suri has spent more than 24 years in imaging sciences, especially in medical
imaging modalities and its fusion. He has published more than 200 technical papers
(no abstracts) in body imaging, specifically MR, CT, x-ray, ultrasound, PET,
SPECT, elastography, and molecular imaging. Dr. Suri has worked at Siemens
Research, Philips Research, Fischer Research Divisions, and Eigen’s Imaging Divi-
sions as a scientist, senior director of R&D, and chief technology officer. He has
submitted more than 30 U.S./European patents on medical imaging modalities. Dr.
Suri has also written 17 collaborative books on body imaging. He is a lifetime mem-
ber of Tau Beta Pi, Eta Kappa Nu, and Sigma Xi and is a member of NY Academy of
Sciences, the Engineering in Medicine and Biology Society, the American Associa-
tion of Physics in Medicine, the SPIE, and the ACM. Dr. Suri is also a Senior Mem-
ber of the IEEE. He is on the editorial board or a reviewer of Real Time Imaging,
Pattern Analysis and Applications, Engineering in Medicine and Biology Magazine,
Radiology, Journal of Computer Assisted Tomography, IEEE Transactions on
Information Technology in Biomedicine, and IASTED Imaging Board. He has also
chaired biomedical imaging tracks at several international conferences and has
given more than 40 international presentations and seminars. Dr. Suri has been
listed in Who’s Who and was a recipient of the President’s Gold Medal in 1980. He
is also a Fellow of American Institute of Medical and Biological Engineering and
ABI. He is visiting faculty at the University of Exeter, Exeter, United Kingdom, the
University of Barcelona, Spain, and Kent State, Ohio, and is the director of the med-
ical imaging division at Jebra Wellness Technologies. Dr. Suri is on board of direc-
tors of Biomedical Technologies Inc. and Cardiac Health Inc. He received a B.S. in
computer engineering from Maulana Azad College of Technology, Bhopal, India,
an M.S. in computer sciences from the University of Illinois, Chicago, a Ph.D. in
electrical engineering from University of Washington, Seattle, and an M.B.A. from
the Weatherhead School of Management, Case Western Reserve University,
Cleveland.
Chirinjeev Kathuria has a B.Sc., with a specialization in U.S. health care policy
and administration, and an M.D. from Brown University. He also has an M.B.A.
from Stanford University. Dr. Kathuria has had measurable success in building
businesses that impact world economies and shift business models. He has
cofounded and helped build many businesses, which have generated shareholder
wealth and jobs. Dr. Kathuria and his affiliated companies have been featured on
many television programs and in media publications. He has extensive experience in
the health care industry and has consulted to a broad range of organizations in the
United States, Europe, and Asia. Dr. Kathuria also helped develop Arthur D. Little
biotechnology and health care policy practice in Europe. He conducted a compara-
415
tive analysis of the European and U.S. biotechnology industries resulting in a paper
entitled “Biotechnology in the Uncommon Market,” which was published in Bio-
technology magazine in December 1992 which helped change at that time the cur-
rent thinking of biotechnology development. Dr. Kathuria’s coauthored papers
include “Selectivity Heat Sensitivity of Cancer Cells,” “Avascular Cartilage as an
Inhibitor to Tumor Invasion,” and “Segmentation of Aneurysms Via Connectivity
from MRA Brain Data,” the latter of which was published in the Proceedings of the
International Society for Optical Engineering in 1993.
Ruey-Feng Chang received a B.S. in electrical engineering from National Cheng
Kung University, Tainan, Taiwan, ROC, in 1984, and an M.S. in computer and
decision sciences and a Ph.D. in computer science from National Tsing Hua Univer-
sity, Hsinchu, Taiwan, ROC, in 1988 and 1992, respectively. Since 2006, he has
been a professor in the Department of Computer Science and Information Engineer-
ing, National Taiwan University, Taipei, Taiwan, ROC. He was a professor from
1992 to 2006 and served as the chair from 2003 to 2006 of the Department of Com-
puter Science and Information Engineering, National Chung Cheng University,
Chiayi, Taiwan, ROC. His research interests include medical computer-aided diag-
nosis systems, image/video processing and retrieval, and multimedia systems and
communication. Dr. Chang is a member of the IEEE, ACM, SPIE, and Phi Tau Phi.
He received the Distinguished Research Award from the National Science Council
of Taiwan in 2004.
Filippo Molinari received the Italian Laurea and a Ph.D. in electrical engineering
from the Politecnico di Torino, Torino, Italy, in 1997 and 2000, respectively. Since
2002, he has been an assistant professor on the faculty of the Dipartimento di
Elettronica, Politecnico di Torino, where he teaches biomedical signal processing,
biomedical image processing, and instrumentation for medical imaging. His main
research interests include the analysis of strongly nonstationary biomedical signals
and the medical imaging applied to the computer-aided diagnosis. Dr. Molinari
developed several signal and image processing algorithms, especially in the field of
neurosciences and in the functional assessment of disabled subjects.
Aaron Fenster is a scientist and the founding director of the Imaging Research
Laboratories at the Robarts Research Institute, the chair of the Imaging Sciences
Division of the Department of Radiology & Nuclear Medicine, the associate direc-
tor of the Graduate Program in Biomedical Engineering at The University of West-
ern Ontario, and the director of the Imaging Pipeline Platform of the Ontario
Institute for Cancer Research. Currently, he holds a Canada Research Chair-Tier 1
in biomedical engineering. He was the recipient of the 2007 Premier’s Award for
Innovative Leadership. Dr. Fenster’s group has focused on the development of 3-D
ultrasound imaging with diagnostic and surgical/therapeutic applications. His team
developed the world’s first 3-D ultrasound imaging of the prostate and 3-D ultra-
sound guided prostate cryosurgery and brachytherapy. This technology has been
licensed to commercial companies that are distributing it worldwide for cancer ther-
apy and research. Dr. Fenster’s research has resulted in 190 peer-reviewed publica-
tions, 32 patents, and the formation of two companies, for which he has been a
founding scientist.
416 About the Editors
List of Contributors
Viren Amin
Center for Nondestructive Evaluation
283 Applied Sciences Complex II
1915 Scholl Road
Ames, IA 50011-3042
e-mail: vamin@cnde.iastate.edu
Elsa D. Angelini
Institut Telecom
Telecom ParisTech
Department of Signal and Image Processing (TSI)
46 rue Barrault
73013 Paris
France
e-mail: elsa.angelini@telecom-paristech.fr
Sergio Badalamenti
Neurology Service
Ospedale Gradenigo
Corso Regina Margherita 10
10153, Torino
Italy
e-mail: sergio.badalamenti@h-gradenigo.it
Ruey-Feng Chang
Department of Computer Science and Information
Engineering and Graduate
Institute of Biomedical Electronics and
Bioinformatics
Sunita Chauhan
Division of Mechatronics and Design
School of Mechanical and Aerospace Engineering
Nanyang Technological University, North Spine
(N3) Level 2
50 Nanyang Avenue
Singapore 639798
e-mail: mcsunita@ntu.edu.sg
Chii-Jen Chen
Department of Computer Science and Information
Engineering
Dar-Ren Chen
Department of Surgery
Changhua Christian Hospital
Changhua,
Taiwan 500
R.O.C.
Kau-Yih Chiou
Department of Computer Science and Information
Engineering
Bernard Chiu
Robarts Research Institute
100 Perth Drive
London, ON, N6A 5K8
Canada
e-mail: bchiu@imaging.robarts.ca
Kevin D. Costa
Department of Biomedical Engineering
Columbia University ET351
1210 Amsterdam Avenue
New York, NY 10027
United States
e-mail: kdc17@columbia.edu
Christakis Damianou
Frederick University Cyprus
7 Yianni Frederickou
1036, Nicosia
Cyprus
e-mail: cdamianou@cytanet.com.cy
Silvia Delsanto
im3D S.p.A.
Medical Imaging Lab
Via Lessolo 3
10153, Torino
Italy
e-mail: silvia.delsanto@i-m3d.com
Donal Downey
Medical Imaging Department
Royal Inland Hospital
311 Columbia Street, Kamloops
BC, V2C 2T1
Canada
e-mail: ddowney@imaging.robarts.ca
Qi Duan
Department of Biomedical Engineering
Columbia University ET351
1210 Amsterdam Avenue
New York, NY 10027
United States
e-mail: duanqi@gmail.com
Michaela Egger
Robarts Research Institute
100 Perth Drive
London, ON, N6A 5K8
Canada
Marcelo D. Faria
National Laboratory for Scientific Computing (LNCC)
Rio de Janeiro, Brazil
Aaron Fenster
Robarts Research Institute
100 Perth Drive
London, ON, N6A 5K8
Canada
e-mail: afenster@imaging.robarts.ca
Olivier Gerard
Philips France
51 rue Carnot
BP 301
Suresnes, 92156
417
France
e-mail: olivier.gerard@philips.com
Gilson A. Giraldi
National Laboratory for ScientificComputing (LNCC)
Rio de Janeiro, Brazil
Pierangela Giustetto
Neurology Service
Ospedale Gradenigo
Corso Regina Margherita 10
10153, Torino
Italy
e-mail: pgiustetto@gmail.com
Jeffrey W. Holmes
Robert M. Berne Cardiovascular Research Center
University of Virginia
Box 800759, Health System
Charlottesville, VA 22908
e-mail: holmes@virginia.edu
Shunichi Homma
Department of Medicine, Columbia University
Cardiology Division
Ph. 9 East 111
622 W. 168 Street
New York, NY 10032
United States
e-mail: sh23@columbia.edu
Manivannan Jayapalan
c/o Professor M. Ramasubba Reddy
Biomedical Eng. Division
Department of Applied Mechanics
Indian Institute of Technology Madras
Chennai 600036
India
e-mail: jmvannan@yahoo.com,
manivannanj@smail.iitm.ac.in
Wei-Ren Lai
Department of Computer Science and Information
Engineering
National Chung Cheng University
Chiayi
Taiwan 621, R.O.C.
Andrew F. Laine
Department of Biomedical Engineering
Columbia University ET351
1210 Amsterdam Avenue
New York, NY 10027
United States
e-mail: laine@columbia.edu
Anthony Landry
Robarts Research Institute
100 Perth Drive
London, ON, N6A 5K8
Canada
William Liboni
Neurology Service
Ospedale Gradenigo
Corso Regina Margherita 10
10153, Torino
Italy
e-mail: william.liboni@h-gradenigo.it
C. P. Loizou
Department ofComputer Science and Engineering
Intercollege
P.O. Box 51604
3507 Limassol
Cyprus
e-mail: loizou.c@lim.intercollege.ac.cy,
panloicy@logos.net.cy
Filippo Molinari
Biolab
Department of Electronics
Politecnico of Torino
Corso Duca degli Abruzzi 24
10129 Torino
Italy
e-mail: filippo.molinari@polito.it
Woo Kyung Moon
Department of Radiology and Clinical Research
Institute
Seoul National University Hospital
Seoul
Korea
e-mail: moonwk@radcom.snu.ac.kr
Grace Parraga
Robarts Research Institute
100 Perth Drive
London, ON, N6A 5K8
Canada
e-mail: gep@imaging.robarts.ca
Marcia Provenzano
National Laboratory for ScientificComputing (LNCC)
Rio de Janeiro, Brazil
Paulo S. Rodrigues
National Laboratory for ScientificComputing (LNCC)
Rio de Janeiro, Brazil
J. David Spence
Siebens-Drake Building
1400 Western Road
London, ON, N6G 2V2
Canada
e-mail: dspence@robarts.ca
Jasjit S. Suri
Eigen LLC
Grass Valley, CA
Idaho Biomedical Research Institute (IBRI)
Idaho State University
Pocatello, ID 83209
United States
e-mail: jsuri@comcast.net
Zhouping Wei
PET Research & Clinical Sciences
Philips Medical Systems
595 Miner Road
Cleveland, OH 44143
United States
e-mail: zhouping.wei@philips.com
Fuxing Yang
Verathon (formerly Diagnostic Ultrasound Corpo
-
ration)
20001 North Creek Parkway
Bothell, WA 98011
United States
e-mail: fuxing.yang@gmail.com
418 List of Contributors
Index
2-D array scanning, 11
2-D continuous strain imaging system, 167–68
discussion, 184
experimental results, 179
performance evaluation, 181–82
2-D manual tracing, 341
2-D ultrasound imaging, 4
3-D B-mode, 70
3-D mean-offset function, 331
3-D MRI, 3
3-D power Doppler imaging, 70
3-D scanners
endocavity rotational, 7–9
linear mechanical, 6
tilt mechanical, 7
3-D shape prior extraction, 327–33
3-D strain imaging system, 165–84
architecture, 168–79
architecture illustration, 169
data acquisition, 169–70
discussion, 184
experimental protocols, 179
image enhancement via sigmoid mapping,
170
performance evaluation, 181–82
segmentation and, 173–74
segmentation results, 179–80
segmentation subsystem, 170–74
strain features, 174–79
3-D TRUS-guided brachytherapy system,
15–16
calibration methods, 23–24
calibration results, 24–25
defined, 15
evaluation of, 22–28
needle angulation accuracy, 26
needle placement accuracy, 25
needle targeting accuracy, 26
needle tracking accuracy, 26–28
robotic aids, 16
seed implantation accuracy, 28
test phantoms, 22
3-D TRUS imaging system, 16–17
3-D ultrasound datasets, 232
3-D ultrasound-guided prostate therapy,
13–22
3-D TRUS-guided brachytherapy, 15–16
3-D TRUS imaging system, 16–17
calibration of coordinate systems, 20–22
dosimetry, 19–20
early-stage prostate cancer management, 14
needle segmentation, 22
prostate segmentation, 17–19
US-guided brachytherapy, 15
3-D ultrasound imaging, 3–30
2-D ultrasound limitations and, 4
availability, 13
breast lesion classification, 143–61
of carotid arteries, 67–89
dynamic, 11
probes, 5
scanning techniques, 4–5
tracked, with articulated arm sensing, 9
tracked by speckle decorrelation, 10
3-D ultrasound visualization, 11–13
multiplanar reformatting, 11–12
volume rendering techniques, 12–13
3-D US images, 102
ECG-triggered acquisition of, 88
reconstruction of, 72–73
viewing, 73
4-D optical flow motion tracking algorithm,
227
4-D ultrasound imaging, 11
A
Ablatherm, 410
Ablation
brain tumor, 351
cancer tumor, 351
chemical, 403–4
cryoablation, 403
endovenous laser (ELA), 407
focused ultrasound-based, 407–10
HIFU, interfaces effect, 390–95
kidney, 376–85
liver, 386–90
microwave, 405–6
419
Ablation (continued)
procedure monitoring, 412
remote, 411
RF, 404–5
thermal, 401–12
Accumulative autocorrelation scheme
(ACC-US), 193
Acoustical monitoring, 369–70
Acoustic shadow, lesion, 214
Acoustic tracking, 9
Active appearance model (AAM), 325
Active contours, 318–25
front evolving geometric models, 319
geodesic models, 319
level-set method-based geometric, 318–25
parametric, 318
region-based, 321–25
tuning geometric, 319–21
See also Prostate analysis
Adaptive speckle reduction (ASR), 229
Adaptive weighted median filter (AWMF), 229
American Society of Echocardiography (ASE)
standard, 262
Analysis of Variance (ANOVA), 79, 80
Anatomic M-mode, 270–71
Angular second moment, 97
Anisotropic diffusion, 228–30
concept, 229
filtering, 38, 39, 44–45, 148
heat diffusion type dynamic equation, 229
Aortic area, 286
Aortic ejection clicks, 292
Area
difference, 167
lesion, 213, 219
Artificial neural network (ANN), 194
Ascultatory areas, 285–86
Atherosclerosis, 112
ATL HDI-5000, 94–95, 105, 107
Atrial septal defects (ASDs), 293
Attenuation measurement, 368, 374–76
as function of thermal dose, 374–76
variable attenuation, 376
Auscultation, 294
Autocorrelation matrix with five frames
(ACC5-US), 194
Automated boundary detection, 262–63
Automatic lesion classification, 189–220
discussion and conclusions, 218–20
five-step methodology, 212–17
introduction, 189–91
morphological chains, 211–12
nonextensive segmentation approaches,
200–211
performance evaluation, 217–18
related works, 191–98
theoretical background, 198–212
Tsallis entropy, 198–200
Autoregressive (AR), 300
modeling, 305–6
moving average (ARMA), 300
B
Bayesian-based regularizers, 320
Bayesian interface, segmentation in, 334–38
Beam angle statistics, 151–53
defined, 151
different order moments, 153
K-curvature, 151
variations, 155
Benign prostate hyperplasia (BPH), 376
Best-fit ellipse computation, 154–55
Bilinear TFRs, 300
Bioheat transfer equation (BHTE), 352, 353
application, 358
without bubble effects, 353
Blind source separation (BSS), 299
Blood-brain barrier opening, 351
Boltzman-Gibbs (BG) entropy, 191, 198
Bootstrap, 189, 190, 191
Boundary tracking, 242
Boundary value formulation, 316
Brachytherapy
3-D TRUS-guided, 15–16, 22–28
seed implantation, 29
US-guided, 15
Brain tumors
ablation, 351
MRI images, 356
Breast cancer, 143, 165
Breast lesion classification, 143–61
with 3-D ultrasound, 143–61
beam angle statistics, 151–53
best-fit ellipse computation, 154–55
CAD system architecture, 147–56
criteria, 151
introduction, 143–45
level set segmentation method, 145–47
strategy, 153–56
true/fitted lesion similarity measurement,
155–56
B-scan views, 232
420 Index
C
Calibration
of coordinate systems, 20–22
fiducial localization error (FLE), 23–24
fiducial registration error (FRE), 23, 24
results, 24–25
target registration error (TRE), 23, 24
Cancer tumor ablation, 351
Cardiac motion analysis, 227–43
anisotropic diffusion, 228–30
dynamic information from optical flow,
237–42
real-time 3-D echocardiography, 228
real-time 3-D US with optical flow, 230–37
summary, 243
Cardiovascular diseases (CVDs), 111
Carotid artery
anatomy and pathology, 112–13
ultrasound analysis principles, 113–15
Carotid artery 3-D US imaging, 67–89
image viewing, 73
introduction, 67–68
magnetically tracked free-hand, 71–72
mechanical linear, 69–70
plague volume measurement, 73–87
reconstruction, 72–73
scanning techniques, 69–72
trends and future developments, 87–89
Carotid artery US
conventional, limitations of, 68
despeckle filtering and, 47
distance measures, 49–50, 51–54
image quality evaluation metrics, 50, 54–56
image recording, 47
kNN classifier, 40, 50, 54
material, 47
methodology, 47–51
quality evaluation, 93–108
results, 51–57
texture analysis, 48–49, 51–54
univariate statistical analysis, 50, 54
visual evaluation by experts, 50–51, 56–57
Carotid plaques
automated segmentation, 79–81
border irregularity measurement, 115
change, 85
contours, 89
dimension measurement, 115
distribution calculation, 86
echolucent, 137, 139
gray-scale classification, 115
imaging, 134–38
local distribution/change, 83–86
lumen boundary, 82
morphological characterization, 67
progression analysis, 76
progression and regression monitoring, 75
relative mean volume, 77
roughness, 82
segmentation, 73–74
segmentation analysis results, 81
stable, 136–37
surface morphology, 82–83
types, 95–96, 114–15
ultrasound analysis, 114–15
unstable, 137–38
volume measurement, 73–87
volume measurements accuracy, 77–78
volume measurement variability, 78–79
Carotid wall
3-D maps, 85–86
IMT, 111
local distribution/change, 83–86
mean, 85
normal, 113–14
segmentation, 122–23
surface reconstruction from polygonal
slices, 83
thickness, 87
US imaging, 112–15
Cartesian coordinates, 237, 238
Cavitation
probability of (POC), 386, 387
threshold, 378
Centerline method, 268–69
Chain rule, 171
Chemical ablation, 403–4
Choi-Williams distribution (CWD), 300–305
kernel, 305
of PCG, 306
Circular gradient vector (CGV), 264
Circularity, lesion, 214, 219
Clicks, 292–93
ejection, 292
nonejection, 293
Clustering-based regularizers, 320
Coherent nonlinear anisotropic diffusion
filtering, 46
Color kinesis method, 269–70
Completely user-independent layer extraction.
See CULEX
Complexity-based gating, 299–300
Index 421
Computed tomography (CT), 3
Computer-aided diagnosis (CAD), 143, 144,
145
beam angle statistics, 151–53
classification strategy, 153–56
data acquisition, 148
for improving diagnostic accuracy, 144
performance evaluation, 158–59
preprocessing subsystem architecture,
148–49
proposed algorithm, 195
segmentation subsystem based on level set
framework, 149–50
similarity measure analysis, 156–57
system architecture, 145, 147–56
system architecture illustration, 147
Computer-generated boundary (CGB), 125
Confidence interval (CI), 133
for average segmentation, 126
for mean segmentation, 134
Continuous murmur, 290
Continuous wavelet transform (CWT), 300,
302–3
coefficient, 302
resolution, 303
Contour difference, 166
normalized, 177–78
value use, 167
Contours, tracing, 268
Contractility, 250
Contrast-to-noise ratio (CNR), 289, 386, 388
Coordinate systems, 238–39
calibration, 20–22
Cartesian, 238–39
for data acquisition and computation, 239
Correct segmentation rate (CSR), 339
Correlation-based optical flow, 231
Coupling-surfaces regularizers, 321
Crescendo, 290
Crescendo-decrescendo, 290
Crossed-planes approach, 11
Cryoablation, 403
C-scan views, 232
Cube-view approach, 12, 73
CULEX
algorithm structure, 118–24
block diagram, 119
characterization and image databases,
125–28
performance, 137, 138
performance comparison, 132
preservation of pixel fuzziness, 123
ROI extraction, 118–22
CULEX segmentation
of CCA images, 123
error, 126–27, 131
example, 135
expanded vision, 124
lumen and carotid wall, 122–23
stable plaques, 136
strategy, 123–24
unstable plaques, 138
D
Decrescendo, 290
Despeckle filtering, 40–47
in carotid artery US imaging, 37–60
diffusion, 44–46
evaluation, 51
findings summary, 58
geometric, 43
homomorphic, 44
limitations, 39–40
local statistics, 41–42
maximum homogeneity over a pixel
neighborhood, 42–43
median, 42
techniques, 38
wavelet, 46–47
Diastole, 285
Diffusion filtering, 44–46
anisotropic, 44–45, 148
coherent nonlinear anisotropic, 46
Direct tracking, 242
Discrete dynamic contour (DDC), 17, 19
Disc summation method, 258, 276
Distance measures, 49–50, 51–54
Doppler index, 250
Dosimetry, 19–20
Double Stimulus Continuous Quality Scale
(DSCQS), 100
Dual level set, 159–60
Dynamic cardiac information, 237–42
coordinate systems, 238–39
data, 240
estimation of myocardial field, 242
measurements, 239
from optical flow, 237–42
results and discussion, 240–41
E
Early diastolic murmur, 290
Early systolic murmur, 290
Echocardiograms, edge detection, 265
422 Index
Echocardiographic examinations, 257–63
left ventricular dp/dt, 260
measurements and calculations, 258–62
RT LV volume, 262–63
Echocardiography, 247–76
2-D, 273
RT 3-D, 228, 272–76
Echolucent plaques, 137, 139
Eigenvalues
decomposition, 331
histogram, 332
Eikonal equation, 149, 316
Ejection clicks, 292
Ejection phase indices, 250–51
ejection fraction, 250–51
fractional shortening, 250–51
myocardial performance index, 251
See also LV
Elastography, 166
Elliptic-normalized circumference (ENC), 196
Elliptic-normalized skeleton (ENS), 196, 197
End diastole (ED), 230, 266
Endocavity rotational 3-D scanners, 7–9
Endovenous laser ablation (ELA), 407
End systole (ES), 230, 266
End systolic pressure-volume relationships
(ESPVR), 252–56
assessment using echocardiography, 254–55
curvilinear, 253
determination, 253
fundamental principle, 252
linear, 253
preload recruitable stroke work, 256
representation, 252
stroke work, 255
End systolic wall stress (ESWS), 260
Entropic index, 199
Entropy
BG, 191, 198
extensive, 199
q, 200
Shannon, 218
subextensive, 199
superextensive, 199
Tsallis, 198–200
Error summation (Minkowski metric), 98–99
Eulerian Hamilton-Jacobi equation, 146, 172
Exercise, 295
Expert-outlined boundaries (EOBs), 125
CGB behavior and, 125
sample mean, 126
Expiration, 295
Exponential distribution, 305
Extensive entropy, 199
F
Fast spoiled gradient (FSPGR), 381
Fiducial localization error (FLE), 23–24
Fiducial registration error (FRE), 23, 24
First-order statistics filtering, 41–42
Fisher discriminant analysis (FDA), 309
Focal ultrasound surgery robots (FUSBOTs),
410–11
for breast surgery, 410
defined, 409
for neurosurgery, 410
for urological organ and stomach cancer
surgeries, 410
Focused ultrasound-based ablation, 407–10
Fourier power spectrum (FPS), 49
Fractal dimension texture analysis (FDTA), 49
Fractional shortening, 250–51
Free-hand scanning
3-D carotid US imaging, 71–72
with acoustic tracking, 9
with magnetic field sensing, 10
need for improvement, 88
with position sensing, 9–10
without position sensing, 11
Fresnel-Kirchhoff diffraction theory, 408
Front evolution, 315–16
Front evolving geometric models of active
contours, 319
Frost filter, 40
Full-field OF estimation, 242
Full-field OF estimation with smoothing, 242
Full matrix array, 273
Fuzzy c-means (FCM), 190
Fuzzy inherence rules, 264
Fuzzy membership functions, 264
Fuzzy systems, 308
G
Gallop sounds, 291–92
Gaussian distribution, 336
Gaussian smoothing kernel, 81
Geodesic active contour models, 319
Geometric average error (GAE), 99
Geometric filtering, 43
Gf4d filter, 43
Gradient recalled acquisition (GRASS), 380
Gradient values, 239
Graphical user interface (GUI), 127, 128
Gray level difference statistics (GLDS), 48
Index 423