Pattern Recognition and Signal Analysis in Medical Imaging

By

  • Anke Meyer-Baese, Department of Scientific Computing, Florida State University, USA
  • Volker Schmid, Department of Statistics, Ludwig-Maximilians-University, Munich, Germany
  • Anke Meyer-Baese, Department of Scientific Computing, Florida State University, USA

Medical Imaging has become one of the most important visualization and interpretation methods in biology and medecine over the past decade. This time has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying medical images. This has led to a huge growth in the application of digital processing techniques for solving medical problems. Design, implementation, and validation of complex medical systems requires a tight interdisciplinary collaboration between physicians and engineers because poor image quality leads to problematic feature extraction, analysis, and recognition in medical application. Therefore, much of the research done today is geared towards improvement of imperfect image material. This important book by academic authority Anke Meyer-Baese compiles, organizes and explains a complete range of proven and cutting-edge methods, which are playing a leading role in the improvement of image quality, analysis and interpretation in modern medical imaging. These methods offer fresh tools of hope for physicians investigating a vast number of medical problems for which classical methods prove insufficient.
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Audience

professors and graduate students in biomedical and electrical engineering, academic researchers, medical imaging professionals

 

Book information

  • Published: October 2003
  • Imprint: ACADEMIC PRESS
  • ISBN: 978-0-12-493290-6


Table of Contents

Foundations of Medical Imaging; Feature Selection and Extraction; Theory of Subband Decomposition and Wavelets; The Wavelet Transform in Medical Imaging; Genetic Algorithms; Statistical Pattern Recognition; Syntactic Pattern Recognition; Neural Networks; Theory; Neural Networks: Applications; Fuzzy Logic: Theory and Clustering Algorithms; Computer Aided Diagnosis Systems