Index
383
anatomical imaging, 350–351
cancer tumor detection, 347–348
functional brain mapping, 348–349
functional heart imaging, 349–350
blurring effects, 351
vs. CT, 352–353
description, 339
detectors, 344–345
fan-beam detection, 344
feature extraction, 351–352
features, 353
functional imaging, 341
image formation, 346–347
imager configuration, 343
image registration, 351–352
vs. MRI, 352–353
noise sources, 351
parallel beam detection, 345
PET/CT combination, 352
physical and physiological principles
degeneration process, 341
positron annihilation, 340
radioactive substances, 339
radionucleotide production, 340–341
positron emission, 342
radioactive detection, 343–345
radioactive labeling, 339
radioisotopes
fluorodeoxyglucose (FDG), 340–341
half-lives, 341
scanning, 344
scintigraphy, 345
signal acquisition, 342–345
significance, 347
vs. ultrasonic images, 352–353
wavelet analysis, 352
Preexcitation, 189
Purkinje fibers, 175
Q
Quad-tree algorithm, 76–77
R
Radiculopathy, 227
Radiolucent, X-ray imaging, 261
Radiopaque, X-ray imaging, 261
Rapid eye movement (REM), 202
Reflection tomography
CT, 251–252
ultrasound imaging
Doppler ultrasound imaging, 327–329
mathematical methodology, 325–326
physical setup, 325
sonogram, heart, 326–327
Region growing, 75–76
Region segmentation
using luminance thresholding, 73–75
quad-tree algorithm, 76–77
region growing, 75–76
Respiratory signals, 242–244
Right-bundle-branch block (RBBB), 187–188
RSR’ complex, 188
S
Sampling and Nyquist rate, 26–27
Sarcomere, 221
Scaling property, 26
Sharpening filters
Butterworth high-pass filters, 61
derivative filters, 56–58
high-boost filters, 54–56
high-pass filter, 53–54
ideal high-pass filters, 60
Short-time Fourier transform (STFT)
disadvantages, 85
magnitude of DFT of three signals, 79–80
shortcomings of relying only on magnitude,
81–82
two signals in time, 79–80
Sigmoid neural networks
activation function, 146–147
backpropagation algorithm, 147–148
momentum, 148–149
Signal
analog, 4
1-D, 3
definition, 3
digital, 6–7
digital images
image capturing, 9
image histogram, 11–13
image representation, 9–11
discrete, 4–5
feature extraction, 8
multidimensional, 4
processing and transformation, 7–8
Signal and image processing methods
complexity analysis
entropy, 104
fractal dimension, 102–103
signal complexity and signal mobility,
101–102
wavelet measures, 103–104
cosine transform, 104–107
information theory
data representation and coding,
116–117
entropy, 114–116
Hoffman coding, 117–118
registration of images, 118–121
383
anatomical imaging, 350–351
cancer tumor detection, 347–348
functional brain mapping, 348–349
functional heart imaging, 349–350
blurring effects, 351
vs. CT, 352–353
description, 339
detectors, 344–345
fan-beam detection, 344
feature extraction, 351–352
features, 353
functional imaging, 341
image formation, 346–347
imager configuration, 343
image registration, 351–352
vs. MRI, 352–353
noise sources, 351
parallel beam detection, 345
PET/CT combination, 352
physical and physiological principles
degeneration process, 341
positron annihilation, 340
radioactive substances, 339
radionucleotide production, 340–341
positron emission, 342
radioactive detection, 343–345
radioactive labeling, 339
radioisotopes
fluorodeoxyglucose (FDG), 340–341
half-lives, 341
scanning, 344
scintigraphy, 345
signal acquisition, 342–345
significance, 347
vs. ultrasonic images, 352–353
wavelet analysis, 352
Preexcitation, 189
Purkinje fibers, 175
Q
Quad-tree algorithm, 76–77
R
Radiculopathy, 227
Radiolucent, X-ray imaging, 261
Radiopaque, X-ray imaging, 261
Rapid eye movement (REM), 202
Reflection tomography
CT, 251–252
ultrasound imaging
Doppler ultrasound imaging, 327–329
mathematical methodology, 325–326
physical setup, 325
sonogram, heart, 326–327
Region growing, 75–76
Region segmentation
using luminance thresholding, 73–75
quad-tree algorithm, 76–77
region growing, 75–76
Respiratory signals, 242–244
Right-bundle-branch block (RBBB), 187–188
RSR’ complex, 188
S
Sampling and Nyquist rate, 26–27
Sarcomere, 221
Scaling property, 26
Sharpening filters
Butterworth high-pass filters, 61
derivative filters, 56–58
high-boost filters, 54–56
high-pass filter, 53–54
ideal high-pass filters, 60
Short-time Fourier transform (STFT)
disadvantages, 85
magnitude of DFT of three signals, 79–80
shortcomings of relying only on magnitude,
81–82
two signals in time, 79–80
Sigmoid neural networks
activation function, 146–147
backpropagation algorithm, 147–148
momentum, 148–149
Signal
analog, 4
1-D, 3
definition, 3
digital, 6–7
digital images
image capturing, 9
image histogram, 11–13
image representation, 9–11
discrete, 4–5
feature extraction, 8
multidimensional, 4
processing and transformation, 7–8
Signal and image processing methods
complexity analysis
entropy, 104
fractal dimension, 102–103
signal complexity and signal mobility,
101–102
wavelet measures, 103–104
cosine transform, 104–107
information theory
data representation and coding,
116–117
entropy, 114–116
Hoffman coding, 117–118
registration of images, 118–121