Compression of Biomedical Images and Signals - Hardcover

Über die Autorin bzw. den Autor

Dr. Amine Naït-Ali is an Associate Professor at the University Paris 12 (France), and a member of the Laboratory LISSI. His research interests are focused on physiological signal processing and analysis, optimisation using metaheuristics, none linear system modeling, biosignal and medical image compression.

Dr. Christine Cavaro-Ménard is an Associate Professor at the University of Angers (France), and a member of the Laboratory LISA. Her research interests include medical image processing (segmentation, classification, texture analysis, registration) for diagnosis assistance, medical image compression and quality evaluation of compressed medical images.

Von der hinteren Coverseite

During the last decade, image and signal compression for storage and transmission purpose has seen a great expansion. But what about medical data compression? Should a medical image or a physiological signal be processed and compressed like any other data? The progress made in imaging systems, storing systems and telemedicine makes compression in this field particularly interesting. However, this compression has to be adapted to the specificities of biomedical data which contain diagnosis information.
As such, this book offers an overview of compression techniques applied to medical data, including: physiological signals, MRI, X-ray, ultrasound images, static and dynamic volumetric images.
Researchers, clinicians, engineers and professionals in this area, along with postgraduate students in the signal and image processing field, will find this book to be of great interest.

Aus dem Klappentext

During the last decade, image and signal compression for storage and transmission purpose has seen a great expansion. But what about medical data compression? Should a medical image or a physiological signal be processed and compressed like any other data? The progress made in imaging systems, storing systems and telemedicine makes compression in this field particularly interesting. However, this compression has to be adapted to the specificities of biomedical data which contain diagnosis information.
As such, this book offers an overview of compression techniques applied to medical data, including: physiological signals, MRI, X-ray, ultrasound images, static and dynamic volumetric images.
Researchers, clinicians, engineers and professionals in this area, along with postgraduate students in the signal and image processing field, will find this book to be of great interest.