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Main research areas
- Medical image processing
- Reconstruction of magnetic resonance imaging (MRI) images and sequences, perfusion analysis of oncological diseases
- Processing of speech, writing, and other time series, including prediction
- Segmentation and measurement of geometric parameters in image sequences
- Quantitative analysis in pathology
- Supportive diagnosis and monitoring of disorders/diseases
- Data science
- Health 4.0
Research groups
- The field of biomedical signal processing is dealt with by research groups:
Brain Disease Analysis Laboratory (BDLab) | Signal Processing Laboratory(SPLab)
Partners
- Research institutions and schools: St. Anne‘s Faculty Hospital in Brno, University Hospital Brno, National Telemedicine Center, Academy of Sciences of the Czech Republic, CEITEC, Pompeu Fabra University, Polytechnic University of Madrid, University of Vienna, University of Edinburgh, University of Arizona, University of Science and Technology Beijing, Vienna University of Technology, Dr. A.P.J.Abdul Kalam Technical University, Lucknow, India
Main practical research results
- System of quantitative analysis of hypokinetic dysarthria
- System for evaluation and prediction of motor/non-motor symptoms of Parkinson's disease
- Supportive diagnosis and monitoring system for Parkinson's disease
- System of quantitative analysis of graphomotor difficulties in persons with neurodevelopmental and neurodegenerative diseases
- Supportive diagnosis and evaluation system of graphomotor difficulties
- Remote sleep monitoring system using actigraphy
- System for segmentation and measurement of geometric parameters in image sequences
Main research publications
- Psychometric Properties of Screening Questionnaires for Children With Handwriting Issues
- Non-invasive stimulation of the auditory feedback area for improved articulation in Parkinson's disease
- Vowel Articulation Dynamic Stability Related to Parkinson’s Disease Rating Features: Male Dataset
- Spatially regularized estimation of the tissue homogeneity model parameters in DCE-MRI using proximal minimization
- Advanced Parametrization of Graphomotor Difficulties in School-Aged Children