Pattern Recognition and Signal Analysis in Medical Imaging

The focus of Pattern Recognition and Signal Analysis in Medical Imaging, Second Edition, is the development of integrated systems for use in the clinical sector. These systems, which enable both imaging and automatic assessment of the resulting data, represent one of the most challenging areas in medical imaging. Medical imaging is one of the heaviest funded biomedical engineering research areas. Since the first edition of this book, there has been tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer-aided analytical techniques, coupled with a continuing demand for more information from medical images, has led to a growing application of digital processing techniques in cancer detection and other areas in medicine. This book delves deep into the details of statistical and syntactic pattern recognition, the theory and applications of neural networks, fuzzy logic, and much more. Biomedical engineers, medical physicists, and other professionals in clinical and research settings will benefit from the state-of-the-art treatment of medical imaging in this book. * New edition has been expanded to cover signal analysis* New chapters cover cluster validity techniques, computer-aided diagnosis systems in breast MRI, and spatio-temporal models in MRI and perfusion cardiac vascular MRI* Gives unparalleled insight into the latest pattern recognition and signal analysis technologies, modeling, and applications. Professor in the Department of Scientific Computing at Florida State University. Professor Meyer-Baese has a PhD in Electrical and Computer Engineering and has been active in the field of pattern recognition applied to bioengineering and systems biology problems both in teaching and research for the past twenty years. She is author of over 200 journal and conference publications, and three books. Professor in the Bioimaging Group at the Department of Statistics, Ludwig-Maximilians-University, Munich. Professor Schmid has a PhD in Statistics and is an expert in Bayesian methods and spatial statistics for medical and microscopy imaging. Previously, he was a Postdoctoral Research Fellow at the Institute for Biomedical Engineering, Imperial College, London.