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E-grāmata: Correction Techniques in Emission Tomography [Taylor & Francis e-book]

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Written by an interdisciplinary team of medical doctors, computer scientists, physicists, engineers, and mathematicians, Correction Techniques in Emission Tomography presents various correction methods used in emission tomography to generate and enhance images. It discusses the techniques from a computer science, mathematics, and physics viewpoint.





The book gives a comprehensive overview of correction techniques at different levels of the data processing workflow. It covers nuclear medicine imaging, hybrid emission tomography (PET-CT, SPECT-CT, PET-MRI, PET-ultrasound), and optical imaging (fluorescence molecular tomography). It illustrates basic principles as well as recent advances, such as model-based iterative algorithms and 4D methods. An important aspect of the book is on new and sophisticated motion correction techniques in PET imaging. These techniques enable high-resolution, high-quality images, leading to better imaging analysis and image-based diagnostics.





Reflecting state-of-the-art research, this volume explores the range of problems that occur in emission tomography. It looks at how the resulting images are affected and presents practical compensation methods to overcome the problems and improve the images.

About the Series xi
Foreword xv
List of Contributors xix
1 Introduction 1(8)
Klaus P. Schafers
1.1 Introduction
1(1)
1.2 Principle of emission tomography
2(2)
1.3 Electromagnetic spectrum
4(1)
1.4 Need for correction techniques
4(3)
References
7(2)
I Background 9(40)
2 Biomedical Applications of Emission Tomography
11(20)
Michael Schafers
Sven Hermann
Sonja Schafers
Thomas Viel
Marilyn Law
Andreas H. Jacobs
2.1 The role of imaging in biomedical research and applications
11(2)
2.2 Functional and molecular imaging by emission tomography enables high sensitivity and spatial resolution
13(1)
2.3 Biomedical applications of emission tomography depend on tracers
14(2)
2.4 Applications
16(10)
2.4.1 Preclinical applications
16(1)
2.4.2 Clinical applications
17(1)
2.4.3 Examples of biomedical applications of emission tomography
18(1)
2.4.3.1 Bioluminescence imaging of tumor growth
18(1)
2.4.3.2 Dynamic PET in pharmakodynamic studies
19(1)
2.4.3.3 From mice to men-Non-invasive translational imaging of inflammatory activity in graft- versus-host disease
20(1)
2.4.3.4 PET to quantify catecholamine recycling and receptor density in patients with arrhythmias
22(1)
2.4.3.5 Multiparametric imaging of brain tumors
23(3)
References
26(5)
3 PET Image Reconstruction
31(18)
Frank Wubbeling
3.1 Introduction
31(1)
3.2 Analytical algorithms
32(8)
3.2.1 Mathematical basis
32(3)
3.2.2 Filtered backprojection
35(2)
3.2.3 Implementation: Resolution and complexity
37(1)
3.2.4 Implementation and rebinning
38(1)
3.2.4.1 2D Rebinning
39(1)
3.2.4.2 3D filtered backprojection
40(1)
3.2.5 Limitations
40(1)
3.3 Discrete algorithms
40(7)
3.3.1 ART-Algebraic reconstruction technique
41(1)
3.3.2 EM
42(2)
3.3.3 Computing the system matrix
44(1)
3.3.4 List mode
45(2)
3.4 Summary
47(1)
References
47(2)
II Correction Techniques in PET and SPECT 49(158)
4 Basics of PET and SPECT Imaging
51(16)
Ralph A. Bundschuh
Sibylle I. Ziegler
4.1 Introduction
51(13)
4.1.1 Interaction of photons with matter
52(1)
4.1.1.1 Photoelectric effect
52(1)
4.1.1.2 Compton scattering
52(2)
4.1.2 Photon attenuation
54(3)
4.1.3 Scatter
57(1)
4.1.4 Variation in detector efficiency, normalization
58(1)
4.1.5 Dead time effects (loss of count rate) (PET and SPECT)
59(1)
4.1.6 Partial volume effects (PET and SPECT)
59(1)
4.1.6.1 Spill out
60(1)
4.1.6.2 Spill in
60(1)
4.1.7 Time resolution and randoms (PET only)
61(1)
4.1.8 Collimator effects-Distance dependent spatial resolution (SPECT only)
62(1)
4.1.9 Positron range and annihilation (PET only)
63(1)
References
64(3)
5 Corrections for Physical Factors
67(38)
Florian Buther
5.1 Introduction
67(2)
5.2 Decay correction
69(2)
5.3 Randoms correction
71(2)
5.3.1 Singles-based correction
72(1)
5.3.2 Delayed window correction
72(1)
5.4 Attenuation correction
73(17)
5.4.1 Stand-alone emission tomography systems
77(3)
5.4.2 PET/CT and SPECT/CT systems
80(2)
5.4.3 Attenuation correction artifacts
82(8)
5.5 Scatter correction
90(5)
5.5.1 Energy windowing methods
91(1)
5.5.2 Analytical methods
92(2)
5.5.3 Direct calculation methods
94(1)
5.5.4 Iterative reconstruction methods
95(1)
5.6 Concluding remarks
95(1)
References
95(10)
6 Corrections for Scanner-Related Factors
105(14)
Marc Huismann
6.1 Positron emission tomography
105(7)
6.1.1 Introduction
105(2)
6.1.2 Data normalization
107(1)
6.1.3 Noise equivalent count rates
108(1)
6.1.4 System dead time
108(2)
6.1.5 Partial volume
110(2)
6.2 Single photon emission computed tomography
112(3)
6.2.1 Linearity, center of rotation, and whole body imaging
112(2)
6.2.2 Motion correction
114(1)
References
115(4)
7 Image Processing Techniques in Emission Tomography
119(38)
Fabian Gigengack
Michael Fieseler
Daniel Tenbrinck
Xiaoyi Jiang
7.1 Introduction
119(2)
7.2 Denoising
121(5)
7.2.1 Image domain
122(1)
7.2.2 Fourier transform domain
123(1)
7.2.3 Wavelet transform domain
124(2)
7.3 Interpolation
126(3)
7.4 Registration
129(8)
7.4.1 Categorization
130(1)
7.4.1.1 Nature of transformation
132(1)
7.4.1.2 Similarity measure
133(2)
7.4.2 Validation
135(2)
7.4.3 Software
137(1)
7.5 Partial volume correction
137(7)
7.5.1 The partial volume effect in PET imaging
138(2)
7.5.2 Correction methods
140(4)
7.6 Super-resolution
144(2)
7.7 Validation
146(4)
7.7.1 Intensity-based measures
146(2)
7.7.2 Phantoms
148(1)
7.7.2.1 Hardware
148(1)
7.7.2.2 Software
149(1)
References
150(7)
8 Motion Correction in Emission Tomography
157(28)
Mohammad Dawood
8.1 Introduction
157(3)
8.1.1 Magnitude of motion
158(1)
8.1.1.1 Patient motion
158(1)
8.1.1.2 Respiratory motion
158(1)
8.1.1.3 Cardiac motion
159(1)
8.2 Motion correction on 3D PET data
160(4)
8.2.1 Overview
161(1)
8.2.2 Rigid motion correction
162(1)
8.2.3 Elastic motion correction
163(1)
8.3 Optical flow
164(4)
8.3.1 Image constraint equation
164(2)
8.3.2 Optical flow methods
166(1)
8.3.3 Optical flow in medical imaging
167(1)
8.4 Lucas-Kanade optical flow
168(1)
8.5 Horn-Schunck optical flow
169(1)
8.6 Bruhn optical flow
170(2)
8.7 Preserving discontinuities
172(1)
8.8 Correcting for motion
173(1)
8.9 Mass conservation-based optical flow
174(3)
8.9.1 Correcting for motion
175(2)
References
177(8)
9 Combined Correction and Reconstruction Methods
185(22)
Martin Benning
Thomas Kosters
Frederic Lamare
9.1 Introduction
186(1)
9.2 Parameter identification
187(5)
9.2.1 Compartment modeling
187(2)
9.2.2 4D methods incorporating linear parameter identification
189(1)
9.2.3 4D methods incorporating nonlinear parameter identification
190(2)
9.3 Combined reconstruction and motion correction
192(6)
9.3.1 The advantages of the list mode format
193(1)
9.3.2 Motion correction during an iterative reconstruction algorithm
194(1)
9.3.2.1 Approaches based on a rigid or affine motion model
194(1)
9.3.2.2 Approaches based on a non-rigid motion model
196(2)
9.4 Combination of parameter identification and motion estimation
198(2)
References
200(7)
III Recent Developments 207(56)
10 Introduction Hybrid Tomographic Imaging
209(8)
Hartwig Newiger
10.1 Introduction
209(1)
10.2 Combining PET and SPECT
210(1)
10.3 The combination with MR
211(3)
10.4 Combining ultrasound with PET and SPECT
214(1)
References
215(2)
11 MR-based Attenuation Correction for PET/MR
217(24)
Matthias Hofmann
Bernd Pichler
Thomas Beyer
11.1 Introduction
218(2)
11.2 MR-AC for brain applications
220(4)
11.2.1 Segmentation approaches
220(1)
11.2.2 Atlas approaches
221(3)
11.3 Methods for torso imaging
224(5)
11.4 Discussion
229(5)
11.4.1 The presence of bone
230(1)
11.4.2 MR imaging with ultrashort echo time (UTE)
231(1)
11.4.3 Required PET accuracy
232(1)
11.4.4 Validation of MR-AC methods
232(1)
11.4.5 Truncated field-of-view
232(1)
11.4.6 MR coils and positioning aids
233(1)
11.4.7 User intervention
233(1)
11.4.8 Potential benefits of MR-AC
234(1)
11.4.9 Additional potential benefits of simultaneous PET/MR acquisition
234(1)
11.5 Conclusion
234(1)
References
235(6)
12 Optical Imaging
241(22)
Angelique Ale
Vasilis Ntziachristos
12.1 Introduction
241(3)
12.2 Fluorescence molecular tomography (FMT)
244(7)
12.2.1 Light propagation model
244(1)
12.2.1.1 Photon interaction with biological tissue
244(1)
12.2.1.2 The diffusion approximation
246(1)
12.2.1.3 Model for a fluorescence heterogeneity
248(1)
12.2.2 Reconstruction of the fluorochrome distribution
249(2)
12.3 FMT and hybrid FMT systems
251(6)
12.3.1 Instrumentation
251(1)
12.3.1.1 Illumination
251(1)
12.3.1.2 Detection
252(1)
12.3.1.3 360° projections
252(1)
12.3.2 Multimodal optical imaging
253(1)
12.3.2.1 Optical tomography and MRI
253(1)
12.3.2.2 FMT-XCT
254(3)
References
257(6)
Index 263
Mohammad Dawood is a researcher at the European Institute for Molecular Imaging. He earned a PhD in computer science from the University of Münster. His research interests include motion correction and tumor segmentation in medical imaging as well as biometrics and pattern analysis in image analysis.





Xiaoyi Jiang is a professor at the University of Münster and a scientist at the European Institute for Molecular Imaging. An IEEE senior member and an IAPR fellow, he earned a PhD in computer science from the University of Bern. His research areas include medical imaging analysis, pattern recognition, and computer vision.





Klaus Schäfers is head of the technology group at the European Institute for Molecular Imaging. He earned a PhD in medical physics from the University of Münster. His research interests include quantitative PET, motion detection and correction, high-resolution PET, multimodal molecular imaging techniques, and molecular imaging information in radiation therapy planning.
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