Objective

This project concerns research in image and signal processing methods that can be used to solve basic problems in telemedicine and key application area demonstrator projects within dermatology.

Overview

The rapid development in sensor technology, signal processing methods and parallel computing technology has enabled the physical realization of complex mathematical models in a diversity of scientific and industrial areas. This beginning interdisciplinary convergence of methodologies in science and technology has already had an impact on several industries and is emerging in medical imaging and more generally in telemedicine. It seems very likely that bringing together specialists from the mentioned areas could further boost the development of medical information processing in Denmark. Such considerations also lead to incorporating the disciplines signal processing, scientific computing, and image analysis in the Department of Mathematical Modelling (IMM) together with applied mathematical physics, numerical analysis, operations research, and statistics.

The main objective of the research program is to contribute signal and image processing tools that can add flexibility, effectivity and user friendliness to medical information processing systems and telemedicine. A further objective is to establish graduate training for MSc- and PhD-students in medical signal and image processing.

Telemedicine was defined by the EU AIM program as "The investigation, monitoring and management of patients and the education of patients and staff using systems which allow ready access to expert advice and patient information no matter of where the patient or relevant information is located''. Telemedicine is a rich market place and a rapidly progressing research field with activity at both the EU and DK levels. Several Danish medical informatics groups have participated in EU projects concerning medical databases, human computer interfaces, and medical expert systems. Telemedicine now faces a number of basic problems concerning document retrieval, datamining in distributed databases, and visualization of high-dimensional data. Furthermore there are numerous image and signal processing problems in specific application domains such as dermatology where e.g., diagnostics support systems, pattern recognition, and novelty detection form significant challenges.