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.
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
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.