Biomedical image and signal analysis

The ongoing development of modern medical technologies, such as magnetic resonance imaging, positron-emission or computer tomography, stipulates the need for efficient and effective methods of biomedical data processing and recognition. In line with technological advancement, the shift of contemporary diagnostics towards personalized, predictive, preventive and participatory medicine can benefit from the recent achievements in image processing, computer vision and machine learning techniques. Algorithms and software designed in the Institute of Electronics address these issues in a variety of applications, like e.g. anatomical structures segmentation, vessels geometry modeling, blood flow and magnetic resonance angiography simulation, tissue perfusion quantification, skin lesion detection and categorization and finally diagnosis of voice disorders. Our scientific interests reach beyond medical applications. Automatic classification of barley grains species is an example of a project, where our competences in image segmentation, registration, and color and texture analysis have proven useful.