Meet our researchers
Find out more about what drives the researchers at our division and learn about wide range of applications our interdisciplinary research is connecting.
Presentations and Interviews featuring researchers of the Division Vi3
At our division we perform research on a wide span of applications, from digitalisation in healthcare, biomedical image processing, handwritten text recognition, human-computer interaction, social robotics to computing education research and more. Here you can read an overview of our main research topics.
Visualisation & Interaction
Understanding complex data sets, such as three dimensional images of the human body, can be improved if you can both see the organs in three dimensions and feel them. The first is called visualisation and the second haptics. We develop new, fast, mathematical methods here. One application is surgery planning.
Medicine & healthcare
Different types of images are important for medical diagnostics and computers can assist in the analysis of such images. In co-operation with radiologists, we develop methods for medical image analysis. Health care personnel must nowadays use computers for journals, examination results, and administration. We develop information systems that improve the efficiency of medical information systems.
Manual counting and measuring in microscopic images is very time consuming. Therefore, we develop automatic image analysis methods for microscopy. The images can be two or three dimensional and the sources can be light, fluorescence, or electron microscopes. The objects to measure can be cancer cells, proteins, or wood fibres and the purpose diagnostics or quality control.
Usability & IT Systems
There is often need for improvement of the usability of IT-systems in large organisations. We develop such improvements based on the theories from the research field human-computer interaction. We also study human behaviour in complex dynamic systems, such as systems for intensive care units, traffic control, and industrial processes, using control theory as a suitable language.
Humanities & Industry
Large numbers of historical handwritten texts have now been digitised. We develop methods to analyse and explore these images. Three dimensional analysis of wood fibre based materials, especially composites, is one of our specialities. We also develop new better ways to display the railway network to traffic controllers and to help industry use image analysis for quality control.
Even though a major fraction of vi2's projects fall within health care, medicine and biology, we also have projects in a wide range of other application fields, most of which we can classify as either humanities or industry.
Ethics & Sustainability
Progress in information and communication technology creates unpredictable ethical problems. One example is electronic patient records that improve medical care but risk the loss of personal integrity. Ever new versions of gadgets and storing data forever create sustainability problems. We create tools to help predict these types of problems when developing new systems.
Images consist of a number of separate points (pixels). Standard geometrical concepts, such as distance and lines must thus be defined discretely. We create and develop such basic definitions. Pixels in two or three dimensions are usually square or cubic, respectively. Theoretically we can prove that there are better shapes and we develop methods for using them.
Education & Didactics
Professionals in information and communication techniques need knowledge within many areas in addition to computer science. Examples are ethics, critical thinking, and international co-operation. We develop research based teaching methods both for industries and universities to achieve this. We also investigate and develop theories of learning and interfaces for efficient distance education.
Methods for Image Data Analysis
Many challenges in automated image analysis are common for all types of applications: how to handle variations in image quality, how to compare images, how to select, or learn, most suitable representations to reach the best performance, and how to understand and interpret results of the automated analysis. We aim at addressing some of these challenges, by developing robust and generally applicable methods; often evaluating them in the context of medical and biomedical applications.