Medical imaging is one of the heaviest funded biomedical engineering research areas. The second edition of Pattern Recognition and Signal Analysis in Medical Imaging brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data.
Since the first edition, 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 need to derive more information from medical images, has led to a growing application of digital processing techniques in cancer detection as well as elsewhere in medicine.
This book is an essential tool for students and professionals, compiling and explaining proven and cutting-edge methods in pattern recognition for medical imaging.
Rezensionen / Stimmen
"The second edition of this book brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data...This book is an essential tool for students and professionals, compiling and explaining proven and cutting-edge methods in pattern recognition for medical imaging." --Zentralblatt MATH 1284-1
Auflage
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science Publishing Co Inc
Zielgruppe
Für Beruf und Forschung
Biomedical engineers; Electrical and electronics engineers; medical physicists; clinical and medical professionals; biomathematicians
Illustrationen
Approx. 150 illustrations
Maße
Höhe: 235 mm
Breite: 191 mm
Gewicht
ISBN-13
978-0-12-810116-2 (9780128101162)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
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. Her research has been sponsored by NIH, NSF and private foundations and she won many international and national research awards. 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.
Autor*in
Department of Scientific Computing, Florida State University, USA
Department of Statistics, Ludwig-Maximilians-University, Munich, Germany
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
