Edical Image Indexing And Compression Based On Vector Quantization Image Retrieval Efficiency Evaluation
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Medical Image Indexing and Compression Based on Vector Quantization: Image Retrieval Efficiency Evaluation
This paper addresses the problem of efficient image retrieval from a compressed image database, using information derived from the compression process. Images in the database are compressed applying two approaches: Vector Quantization (VQ) and Quadtree image decomposition. Both are based on Konohen's Self-Organizing Feature Maps (SOFM) for creating vector quantization codebooks. However, while VQ uses one codebook of one resolution to compress the images, Quadtree decomposition uses simultaneously 4 codebooks of four different resolutions. Image indexing is implemented by generating a Feature Vector (FV) for each compressed image. Accordingly, images are retrieved by means of FVs similarity evaluation between the query image and the images in the database, depending on a distance measure. Three distance measures have been analyzed to assess FV index similarity: Euclidean, Intersection and Correlation distances. Distance measures efficiency retrieval is evaluated for different VQ resolutions and different Quadtree image descriptors. Experimental results using real data, esophageal ultrasound and eye angiography images, are presented.
M-Health
Author: Robert Istepanian
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-01-04
M-health can be defined as the ‘emerging mobile communications and network technologies for healthcare systems.' This book paves the path toward understanding the future of m-health technologies and services and also introducing the impact of mobility on existing e-health and commercial telemedical systems. M-Health: Emerging Mobile Health Systems presents a new and forward-looking source of information that explores the present and future trends in the applications of current and emerging wireless communication and network technologies for different healthcare scenaria. It also provides a discovery path on the synergies between the 2.5G and 3G systems and other relevant computing and information technologies and how they prescribe the way for the next generation of m-health services. The book contains 47 chapters, arranged in five thematic sections: Introduction to Mobile M-health Systems, Smart Mobile Applications for Health Professionals, Signal, Image, and Video Compression for M-health Applications, Emergency Health Care Systems and Services, Echography Systems and Services, and Remote and Home Monitoring. This book is intended for all those working in the field of information technologies in biomedicine, as well as for people working in future applications of wireless communications and wireless telemedical systems. It provides different levels of material to researchers, computing engineers, and medical practitioners interested in emerging e-health systems. This book will be a useful reference for all the readers in this important and growing field of research, and will contribute to the roadmap of future m-health systems and improve the development of effective healthcare delivery systems.
Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011
Author: Kusum Deep
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-04-13
The objective is to provide the latest developments in the area of soft computing. These are the cutting edge technologies that have immense application in various fields. All the papers will undergo the peer review process to maintain the quality of work.