Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry

Perner P., Salvetti O.

J.3 Life and Medical Sciences  Data Analysis  Computer Vision  Medical Imaging 

The automatic analysis of signals and images together with the characterization and elaboration of their representation features is still a challenging activity in many relevant scientific and hi-tech fields such as medicine, biotechnology, and chemistry. Multidimensional and multisource signal processing can generate a number of information patterns which can be useful to increase the knowledge of several domains for solving complex problems. Furthermore, advanced signal and image manipulation allows relating specific application problems into pattern recognition problems, often implying also the development of KDD and other computational intelligence procedures. Nevertheless, the amount of data produced by sensors and equipments used in biomedicine, biotechnology and chemistry is usually quite huge and structured, thus strongly pushing the need of investigating advanced models and efficient computational algorithms for automating mass analysis procedures. Accordingly, signal and image understanding approaches able to generate automatically expected outputs become more and more essential, including novel conceptual approaches and system architectures. The purpose of this third edition of the International Conference on Mass Data Analysis of Signals and Images in Medicine, Biotechnology, Chemistry and Food Industry (MDA 2008; www.mda-signals.de) was to present the broad and growing scientific evidence linking mass data analysis with challenging problems in medicine, biotechnology and chemistry. Scientific and engineering experts convened at the workshop to present the current understanding of image and signal processing and interpretation methods useful for facing various medical and biological problems and exploring the applicability and effectiveness of advanced techniques as solutions. The primary goal of the conference was to disseminate this knowledge to a multidisciplinary community and encourage cooperative proactive collaboration in all the interested fields. We were pleased to see that the idea of the conference was taken up by a growing number of researchers and that we could start to bundle the activities in this area. We appreciate the help and understanding of the editorial staff at Springer, and in particular Alfred Hofmann, who supported the publication of these proceedings in the LNAI series. Last, but not least, we wish to thank all the speakers and participants who contributed to the success of the conference. The next International Conferences on Mass Data Analysis of Signals and Images (www.mda-signals.de) will be held in July 2009. We are looking forward to your submissions.