Description
This book deals with the application of nuclear magnetic resonance (NMR [1]) in engineering sciences. Special emphasis is put on methods including spatial resolu-tion (magnetic resonance imaging, MRI). The use of permanent-magnet systems is also treated.
The engineering competence was brought in by numerous colleagues that are acknowledged in the preface. In the common publications [1–23, 25] referred to in the following, details on the engineering background and investigations with other methods are reported.
First, fundamentals of the NMR methods and pertinent data analysis are sum-marized in Chap. 2. Concepts from quantum mechanics are not essential for the understanding of the methods used and are only briefly mentioned at the beginning. However, where helpful for the understanding, the relevant equations are worked out.
Obtaining quantitative results is a key issue. Qualitative evidence, that can already be valuable in medical applications, often represent no progress in engineer-ing sciences. Thus the quantitative relation between the data obtained by discrete inverse Fourier transform of raw data and the continuous function of interest is formulated. The influence of gradient imperfections on velocity measurements is assessed. This is of particular importance for experiments using simpler permanent-magnet systems. Application of a post processing taking corresponding shifts in Fourier space into account is presented. For relaxation measurements on flowing samples, a data analysis including effects of inhomogeneous fields for polarization, excitation, and detection is elaborated.
In the domain of volume-image analysis an efficient implementation of a seg-mentation algorithm is presented. In the cases studied, the procedure gives better results than the standard watershed transformation. For the quantitative analysis of the uniformity of mixtures, the influence of artifacts on the signal variance is calculated. Finally, a method for automatic nonlinear phase correction of volume images is presented. For measurements with low signal-to-noise ratio (SNR), phase correction markedly improves the quantitative analysis.
This book deals with the application of nuclear magnetic resonance (NMR [1]) in engineering sciences. Special emphasis is put on methods including spatial resolu-tion (magnetic resonance imaging, MRI). The use of permanent-magnet systems is also treated.
The engineering competence was brought in by numerous colleagues that are acknowledged in the preface. In the common publications [1–23, 25] referred to in the following, details on the engineering background and investigations with other methods are reported.
First, fundamentals of the NMR methods and pertinent data analysis are sum-marized in Chap. 2. Concepts from quantum mechanics are not essential for the understanding of the methods used and are only briefly mentioned at the beginning. However, where helpful for the understanding, the relevant equations are worked out.
Obtaining quantitative results is a key issue. Qualitative evidence, that can already be valuable in medical applications, often represent no progress in engineer-ing sciences. Thus the quantitative relation between the data obtained by discrete inverse Fourier transform of raw data and the continuous function of interest is formulated. The influence of gradient imperfections on velocity measurements is assessed. This is of particular importance for experiments using simpler permanent-magnet systems. Application of a post processing taking corresponding shifts in Fourier space into account is presented. For relaxation measurements on flowing samples, a data analysis including effects of inhomogeneous fields for polarization, excitation, and detection is elaborated.
In the domain of volume-image analysis an efficient implementation of a seg-mentation algorithm is presented. In the cases studied, the procedure gives better results than the standard watershed transformation. For the quantitative analysis of the uniformity of mixtures, the influence of artifacts on the signal variance is calculated. Finally, a method for automatic nonlinear phase correction of volume images is presented. For measurements with low signal-to-noise ratio (SNR), phase correction markedly improves the quantitative analysis.