Description
Book SynopsisUses the FPT to Solve the Quantification Problem in MRS
An invaluable tool in non-invasive clinical oncology diagnostics
Addressing the critical need in clinical oncology for robust and stable signal processing in magnetic resonance spectroscopy (MRS), Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications explores cutting-edge theory-based innovations for obtaining reliable quantitative information from MR signals for cancer diagnostics. By defining the natural framework of signal processing using the well-established theory of quantum physics, the book illustrates how advances in signal processing can optimize MRS.
The authors employ the fast Padé transform (FPT) as the unique polynomial quotient for the spectral analysis of MR time signals. They prove that residual spectra are necessary but not sufficient criteria to estimate the error invoked in quantification. Instead
Trade Review
"a useful addition to the fields of both magnetic resonance (MR) as well as signal processing. ... immensely useful as a practical resource handbook to dip into from time to time and to find specific advice on issues faced during the course of work in MR techniques for cancer research. ... the best feature of this book is how it positions the very practical area of digital signal processing in the contextual framework of a much more esoteric and fundamental field-that of quantum mechanics. The direct link between quantum-mechanical spectral analysis and rational response functions and the general role of quantum mechanics in signal processing is beautifully brought out in Chapter 2. This chapter alone is worth the price of the book and will especially appeal to a multi-disciplinary audience comprising NMR spectroscopists, atomic and molecular physicists, and physicists who work in the foundations of quantum mechanics." -Kavita Dorai, Contemporary Physics, January 2013
Table of Contents
Basic Tasks of Signal Processing in Spectroscopy. The Role of Quantum Mechanics in Signal Processing. Harmonic Transients in Time Signals. Signal-Noise Separation via Froissart Doublets. Padé Processing for Magnetic Resonance (MR) Total Shape Spectra from in vivo Free Induction Decays (FIDs). Exact Reconstructions of Spectral Parameters by FPT. Machine Accurate Padé Quantification and Exact Signal-Noise Separation. Magnetic Resonance Spectroscopy (MRS) and Magnetic Resonance Spectroscopic Imaging (MRSI) in Neuro-Oncology: Achievements and Challenges. Padé Quantification of Malignant and Benign Ovarian MRS Data. Breast Cancer and Non-Malignant Breast Data: Quantification by FPT. Multiplet Resonances in MRS Data from Normal and Cancerous Prostate. General Discussion. Conclusions and Outlooks.
