next up previous contents
Next: How to contact CBA Up: Introduction Previous: General background   Contents


Summary of research

The objective of the CBA is to ``carry out research and graduate education in computerized image analysis and scientific visualization, both within image processing as such and with the goal of developing better methods, algorithms and systems for applications primarily within biomedicine, forestry and the environmental sciences.''

We are pursuing this objective by running a large number of research projects, ranging from fundamental mathematical methods development to application-tailored developments and testing, the latter mainly in biomedicine and forestry. We are also developing new methods for perceptualization, combining computer graphics, haptics and image processing in new ways.

Our research is organised in a large number, 53, projects of varying size, ranging from a single person part time a few months, to projects involving several persons over several years. There is a lot of interaction between different researchers, typically a person is involved in several different projects in different constellations with internal and external partners. In this context the university affiliation of the particular researchers seldom has any importance.

On the theoretical side, we are founding most of our work on discrete mathematics with fundamental work on skeletons, distances and tesselations in three and more dimensions. Another fruitful theoretical foundation is fuzzy methods.

A fairly large set of projects deal with light microscopy images, developing tools for modern quantitative biology and clinical cancer detection and grading. This has, in addition to many publications, also led to a patent application on improved spectral signal detection in fluorescent microscopy and to a publicly available software tool, BlobFinder, for detecting fluorescent signals in microscopic images.

Going beyond the resolution achievable with light microscopy we work with electron microscopy images. One application is to find viruses in EM images, here the vast search area and the small size of the target structures create great challenges. We are also developing methods for studying the 3D shape of large molecules based on electron tomography. Another imaging modality, providing 3D images of small structure, is X-ray micro-tomography. We are developing methods to use such images to study the internal structure of paper and composites, of trabecular bone as well as bone-implant integration.

On a more macroscopic scale we are working with interactive segmentation of 3D CT and MR images. For this we have developed a toolbox, WISH, which is publicly available. Part of that work also involves haptic interaction, and we have started a large interdisciplinary project aiming to create ``the ultimate haptic system,'' a glove through which a person can feel and manipulate virtual objects. Our projects most clearly related to forestry deal with estimates of timber quality from cameras mounted under harsh conditions in saw mills.

A new approach that we are using in several different application areas is to generate synthetic images that are sufficiently similar to real images to be used for testing algorithms. In that way it is easy to generate many images with known ground truth, solving a big common problem in many applications. Of course, the final programs still need to be tested on real images, but the synthetic images can be of great value in the development process.

Please, see Section 5 for details on our interesting research projects.

Another activity bridging over between research and education is supervision of master thesis projects. This year we had seven such projects completed. Three of those were in collaboration with GE Healthcare, Uppsala, dealing with improved techniques for PET image analysis. The other four spanned a wide range of topics. In Section 3.3, we present these theses.


next up previous contents
Next: How to contact CBA Up: Introduction Previous: General background   Contents