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The automatic analysis of images and signals in medicine, biotechnology, and chemistry is a challenging and demanding field. Signal-producing procedures by microscopes, spectrometers, and other sensors have found their way into wide fields of medicine, biotechnology, economy, and environmental analysis. With this arises the problem of the automatic mass analysis of signal information. Signal-interpreting systems which generate automatically the desired target statements from the signals are therefore of compelling necessity. The continuation of mass analyses on the basis of classical procedures leads to investments of proportions that are not feasible. New procedures and system architectures are therefore required. The scope of the International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology and Chemistry MDA (www.mda-signals.de) is to bring together researchers, practitioners, and industry people who are dealing with mass analysis of images and signals to present and discuss recent research in these fields. The goals of this workshop are to: Provide a forum for identifying important contributions and opportunities for research on mass data analysis on microscopic images Promote the systematic study of how to apply automatic image analysis and interpretation procedures to that field Show case applications of mass data analysis in biology, medicine, and chemistry Topics of interest include (but are not limited to): Techniques and developments of signal and image producing procedures Object matching and object tracking in microscopic and video microscopic images 1D, 2D, and 3D shape analysis and description




This book constitutes the refereed proceedings of the International Conference on Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry, MDA 2006 and 2007, held in Leipzig, Germany..

The topics include techniques and developments of signal and image producing procedures, object matching and object tracking in microscopic and video microscopic images, 1D, 2D and 3D shape analysis, description and feature extraction of texture, structure and location, image segmentation algorithms, parallelization of image analysis and semantic tagging of images from life science applications.

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