Time Frequency And Wavelets In Biomedical Signal Processing

Description:

Biomedical Engineering Time Frequency and Wavelets in Biomedical Signal Processing IEEE Press Series in Biomedical Engineering Metin Akay, Series Editor Endorsed by the IEEE Engineering in Medicine and Biology Society Brimming with top articles from experts in signal processing and biomedical engineering, Time Frequency and Wavelets in Biomedical Signal Processing introduces time-frequency, time-scale, wavelet transform methods, and their applications in biomedical signal processing. This edited volume incorporates the most recent developments in the field to illustrate thoroughly how the use of these time-frequency methods is currently improving the quality of medical diagnosis, including technologies for assessing pulmonary and respiratory conditions, EEGs, hearing aids, MRIs, mammograms, X rays, evoked potential signals analysis, neural networks applications, among other topics. Time Frequency and Wavelets in Biomedical Signal Processing will be of particular interest to signal processing engineers, biomedical engineers, and medical researchers. Topics covered include:

• Time-frequency analysis methods and biomedical applications
• Wavelets, wavelet packets, and matching pursuits and biomedical applications
• Wavelets and medical imaging
• Wavelets, neural networks, and fractals

Table of Contents:

List of Contributors.

Preface.

TIME-FREQUENCY ANALYSIS METHODS WITH BIOMEDICAL APPLICATIONS.

Recent Advances in Time-Frequency Representations: Some Theoretical Foundation (W. Williams).

Biological Applications and Interpretations of Time-Frequency Signal Analysis (W. Williams).

The Application of Advanced Time-Frequency Analysis Techniques to Doppler Ultrasound (S. Marple, et al.).

Analysis of ECG Late Potentials Using Time-Frequency Methods (H. Dickhaus & H. Heinrich).

Time-Frequency Distributions Applied to Uterine EMG: Characterization and Assessment (J. Duchene & D. Devedeux).

Time-Frequency Analyses of the Electrogastrogram (Z. Lin and J. Chen).

Recent Advances in Time-Frequency and Time-Scale Methods (C. Mello & M. Akay).

WAVELETS, WAVELET PACKETS, AND MATCHING PURSUITS WITH BIOMEDICAL APPLICATIONS.

Fast Algorithms for Wavelet Transform Computation (O. Rioul & P. Duhamel).

Analysis of Cellular Vibrations in the Living Cochlea Using the Continuous Wavelet Transform and the Short-Time Fourier Transform (M. Teich, et al.).

Alterative Processing Method Using Gabor Wavelets and the Wavelet Transform for the Analysis of Phonocardiogram Signals (M. Matalgah, et al.).

Wavelet Feature Extraction from Neurophysiological Signals (M. Sun & R. Sclabassi).

Experiments with Adapted Wavelet De-Noising for Medical Signals and Images (R. Coifman & M. Wickerhauser).

Speech Enhancement for Hearing Aids (J. Rutledge).

From Continuous Wavelet Transform to Wavelet Packets: Application to the Estimation of Pulmonary Microvascular Pressure (M. Karrakchou & M. Kunt).

In Pursuit of Time-Frequency Representation of Brain Signals (P. Durka & K. Blinowska).

EEG Spike Directors Based on Different Decompositions: A Comparative Study (L. Senhadji, et al.).

WAVELETS AND MEDICAL IMAGING.

A Discrete Dyadic Wavelet Transform for Multidimensional Feature Analysis (I. Koren & A. Laine).

Hexagonal QMF Banks and Wavelets (S. Schuler & A. Laine).

Inversion of the Radon Transform under Wavelet Constraints (B. Sahiner & A. Yagle).

Wavelets Applied to Mammograms (W. Richardson).

Hybrid Wavelet Transform for Image Enhancement for Computer-Assisted Diagnosis and Telemedicine Applications (L. Clarke, et al.).

Medical Image Enhancement Using Wavelet Transform and Arithmetic Coding (P. Saipetch, et al.).

Adapted Wavelet Encoding in Functional Magnetic Resonance Imaging (D. Healy, et al.).

A Tutorial Overview of a Stabilization Algorithm for Limited-Angle Tomography (T. Olson).

Wavelet Compression of Medical Images (A. Manduca).

WAVELETS, NEURAL NETWORKS, AND FRACTALS.

Single Side Scaling Wavelet Frame and Neural Network (Q. Zhang).

Analysis of Evoked Potentials Using Wavelet Networks (H. Heinrich & H. Dickhaus).

Self-Organizing Wavelet-Based Neural Networks (K. Kobayashi).

On Wavelets and Fractal Processes (P. Flandrin).

Fractal Analysis of Heart Rate Variability (R. Fischer & M. Akay).

Index.

Editor's Biography.