Linköping University | Dept. of Biomedical Engineering | Medical Informatics  
   
Medical Informatics Linköping University


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Research


The overall purpose of systems developed in the field of medical informatics is to extract and present clinically relevant information. Medical information appears in many different forms: Text, Parameters,Value Measurements, Time Courses, Images, Volumes, Image and Volume Sequences. Methods to attain new types of information is continuously being developed and the detail and quality of recorded data is increasing rapidly. Huge amounts of potentially relevant information can be tied to one single patient. In addition it is necessary to be able to integrate and analyze information from a large number of patients and time instances.

This development has led to a situation where we are at risk of drowning in the overwhelming flow of information. To be able to extract the relations that are pertinent in a given situation and to present them in a way that is simple to understand is rapidly becoming the main problem. Efficient solutions of this problem will be crucial components in future health care. To develop principles and methods for such solutions is the goal the research in the field of medical informatics. In particular the research group focuses on the development of systems for medical decision support and medical image analysis.

Ongoing research projects 

3D-4D Medical Image Enhancement Vinnova, Context Vision
Advanced Home Healthcare Environment Vinnova, SITI, ITHS2
Antibiotic Resistance in ICUs
Data to Knowledge in Oncology FORSS
Functional Magnetic Resonance Imaging VRm
Hip Fracture Surgery Simulator Vinnova, Melerit
Similar - The European taskforce creating human-machine interfaces SIMILAR to human-human communication. EU NoE 'SIMILAR'
Semantic Interoperability VR
SemanticMining EU NoE
The Classification Browser
Tensor Signal Processing NiMed, LiU
Risk Factor Analysis
Reduction of Motion Artifacts in MRI VRnt
Automated Hippocampus Segmentation VR
Manifold-Valued Signal Processing VR, LiU

Past research projects 

Analysis of ultrasound images Amersham, Vinnova, NiMed
Digital Mammography MAMEA, Vinnova, NiMed
Analys av MR-bilder med ANN
GALEN/GALEN-IN-USE
Spriterm
TEMEC
Morphological Angiography Vinnova
Learning in High Dimensional Signal Spaces VRnt
HELIOS
KUSIVAR
PT-pol
Vision as Process (VAP) EU Research Project
Stem Cell Motion Analysis SSF
Image Sequence Quality Estimation SSF
 

Editor: Johanna Pettersson
Last update: Wednesday, 02-May-2007 16:29:43 MEST
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