洋書 | 技術書
商品コード:
9780819492579
Spectral Computed Tomography
販売価格(税込):
5,700
円
ポイント:
57
Pt
Bjorn J. Heismann; Bernhard T. Schmidt; Thomas G. Flohr
130 pages; Softcover
2012/10/9
PM226
詳細
Computed tomography (CT) is a widely used x-ray scanning technique. In its prominent use as a medical imaging device, CT serves as a workhorse in many clinical settings throughout the world. It provides answers to urgent diagnostic tasks such as oncology tumor staging, acute stroke analysis, or radiation therapy planning. Spectral Computed Tomography provides a concise, practical coverage of this important medical tool. The first chapter considers the main clinical motivations for spectral CT applications. In Chapter 2, the measurement properties of spectral CT systems are described. Chapter 3 provides an overview of the current state of research on spectral CT algorithms. Based on this overview, the technical realization of spectral CT systems is evaluated in Chapter 4. Device approaches such as DSCT, kV switching, and energy-resolving detectors are compared. Finally, Chapter 5 summarizes various algorithms for spectral CT reconstructions and spectral CT image postprocessing, and links these algorithms to clinical use cases.
Sample Pages (PDF)
Chapter 1. Clinical Motivation for CT
References
Chapter 2. Physics of Spectral CT Measurements
2.1 X-Ray Source
2.2 Object
2.3 Detector
2.3.1 Detector responsivity details
2.4 Spectral Weighting
2.4.1 The linear Radon approximation
2.5 Measurement Results
References
Chapter 3. Spectral CT Algorithms
3.1 Basis Material Decomposition
3.1.1 Projection-based basis material decomposition
3.1.2 Image-based basis material decomposition
3.1.3 Practical implications of the basis material decomposition
3.2 Density and Atomic Number Reconstruction
3.2.1 Theory
3.2.2 Analytical approximation
3.2.3 Numerical solution
3.2.4 Fractional atomic numbers
3.2.5 Algorithm flow chart
3.2.6 Basic imaging properties
3.2.7 Quantitative measurement of chemical solutions
3.2.8 Quantitative reconstruction of body fluids
3.3 Limits of Spectral CT Algorithms
3.3.1 Measurement errors
3.3.2 Algorithmic information transfer
3.4 Comparison of Spectral CT Algorithms
References
Chapter 4. Techniques to Acquire Spectral CT Data
4.1 Use of Different X-Ray Spectra
4.1.1 Slow kV switching
4.1.2 Rapid kV switching
4.1.3 Dual-source CT
4.2 Use of Energy-Resolving Detectors
4.2.1 Dual-layer detectors
4.2.2 Photon-counting detectors
References
Chapter 5. Clinical Applications
5.1 Raw-Data-based Applications
5.1.1 Basic principle
5.1.2 Medical applications of raw-data-based approaches
5.1.2.1 Bone densitometry
5.1.2.2 Monoenergetic images
5.1.2.3 K-edge imaging
5.2 Image-Data-based Applications
5.2.1 Simple techniques: Image mixing, optimized contrast, dual-energy index, and monoenergetic
5.2.1 Medical applications for image-based two-material decomposition
5.2.1 Medical applications for image-based three-material decomposition
5.3 Conclusions
References