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E-raamat: MRI: Essentials for Innovative Technologies [Taylor & Francis e-raamat]

(University of L'Aquila, L'Aquila, Italy)
  • Formaat: 216 pages, 85 Illustrations, black and white
  • Ilmumisaeg: 21-Oct-2019
  • Kirjastus: CRC Press
  • ISBN-13: 9780429106415
  • Taylor & Francis e-raamat
  • Hind: 207,73 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 296,75 €
  • Säästad 30%
  • Formaat: 216 pages, 85 Illustrations, black and white
  • Ilmumisaeg: 21-Oct-2019
  • Kirjastus: CRC Press
  • ISBN-13: 9780429106415
MRI: Essentials for Innovative Technologies describes novel methods to improve magnetic resonance imaging (MRI) beyond its current limitations. It proposes smart encoding methods and acquisition sequences to deal with frequency displacement due to residual static magnetic field inhomogeneity, motion, and undersampling. Requiring few or no hardware modifications, these speculative methods offer building blocks that can be combined and refined to overcome barriers to more advanced MRI applications, such as real-time imaging and open systems.

After a concise review of basic mathematical tools and the physics of MRI, the book describes the severe artifacts produced by conventional MRI techniques. It first tackles magnetic field inhomogeneities, outlining conventional solutions as well as a completely different approach based on time-varying gradients and temporal frequency variation coding (acceleration). The book then proposes two innovative acquisition methods for reducing acquisition time, motion, and undersampling artifacts: adaptive acquisition and compressed sensing. The concluding chapter lays out the authors predictions for the future of MRI.

For some of the proposed solutions, this is the first time the reported results have been published. Where experimental data is preliminary or unavailable, the book presents only numerical solutions. Offering insight into emerging MRI techniques, this book provides readers with specialized knowledge to help them design better acquisition sequences and select appropriate correction methods.

The authors proceeds from the sale of this book will be entirely donated to Bambin Gesù Childrens Hospital in Rome.
I Basic Concepts
1(71)
1 Mathematical Tools
3(24)
1.1 Frequency Encoding and Fourier Transform
3(9)
1.2 FT Properties
12(6)
1.3 Sampling, Interpolation, and Aliasing
18(6)
1.4 Instruments for Image Analysis
24(3)
2 MRI: Conventional Imaging Techniques and Instruments
27(45)
2.1 Magnetic Resonance Phenomenon
28(20)
2.1.1 References Frames
31(1)
2.1.2 Excitation and Resonance
32(3)
2.1.3 Relaxation of Magnetization
35(4)
2.1.3.1 Longitudinal Relaxation
39(1)
2.1.3.2 Transverse Relaxation
40(3)
2.1.4 Signal Detection
43(5)
2.2 Imaging Gradients
48(8)
2.2.1 Frequency Encoding
50(1)
2.2.2 Phase Encoding
50(3)
2.2.3 Slice Selection
53(3)
2.3 Conventional Imaging Techniques
56(8)
2.3.1 Spin Warp Imaging
56(2)
2.3.2 Imaging from Projections
58(6)
2.4 Bandwidth, Sampling, Resolution, and Sensitivity
64(3)
2.5 An MRI Scanner
67(2)
2.6 Bloch Equations and Numerical MRI Simulators
69(3)
II Limitations of Conventional MRI
72(20)
3 Limiting Artifacts for Advanced Applications
73(19)
3.1 Magnetic Field Inhomogeneity
74(7)
3.2 Motion
81(2)
3.3 Undersampling
83(8)
3.4 Summary
91(1)
III Advanced Solutions
92(78)
4 Methods for Magnetic Field Inhomogeneity Reduction
93(28)
4.1 Introduction
94(1)
4.2 Conventional Methods
95(9)
4.2.1 Field Mapping
95(3)
4.2.2 Field Gradients Modulation
98(5)
4.2.3 Some Remarks
103(1)
4.3 An Unconventional Solution
104(15)
4.3.1 Spatial Encoding by Nonconstant Gradients
105(4)
4.3.1.1 Numerical Simulations
109(3)
4.3.1.2 Noise Tolerance
112(7)
4.4 Summary
119(2)
5 Methods to Handle Undersampling
121(49)
5.1 Introduction
121(2)
5.2 Sparse Methods without Restoration
123(6)
5.3 Sparse Methods with Restoration
129(40)
5.3.1 Sample Adaptive Acquisition/Restoration Methods
129(1)
5.3.1.1 Entropy-Based Adaptive Acquisition Method
130(4)
5.3.1.2 Adaptive Acquisition Results
134(4)
5.3.1.3 An Adaptive Acquisition Improvement
138(8)
5.3.2 Sample Independent Acquisition/Restoration Methods
146(1)
5.3.2.1 Compressed Sensing
147(13)
5.3.2.1.1 Compressed Sensing Results
157(3)
5.3.2.1.2 Some Remarks on Compressed Sensing in MRI
159(1)
5.3.2.2 Compressed Sensing on Adaptively Collected Data
160(9)
5.4 Summary
169(1)
IV The Future
170(5)
6 Conclusions and perspectives
171(4)
6.1 Some Hypothesis
173(2)
Bibliography 175(14)
Index 189
Giuseppe Placidi is an assistant professor in Computer Science in the Department of Health Sciences at the University of LAquila. He has authored or co-authored more than 55 papers published in international scientific journals and books, 60 refereed conferences proceedings, and seven patents. He is a member of the IEEE Engineering in Medicine and Biology Society, the IEEE Computer Society, the Italian Group for Electron Spin Resonance (GIRSE), and the Italian Group for Physics of Matter (INFM). Dr. Placidi is also a reviewer for several scientific journals on medical physics and imaging. His research interests include MRI, MRI acquisition sequences, image reconstruction, image analysis, image compression, and information theory.

For more information, see www.giuseppeplacidi.org.