A main challenge of biomedical research in the postgenomic era is the unraveling of the molecular mechanisms of life. This is facilitated by recent advances in molecular probing and imaging technologies, which are having an enormous impact on the basic life sciences and human health care, by enabling a better understanding of disease mechanisms, the development of new biomarkers for early diagnosis, and enhanced preclinical validation of novel treatments in small-animal models as a first step towards clinical implementation.
Current studies into dynamic phenomena at the cellular and molecular levels are generating vast amounts of multiparameter spatiotemporal image data, containing much more relevant information than can be analyzed by human observers. Hence there is a rapidly growing need for automated methods for quantitative analysis of such data, not only to cope with the rising rate at which images are acquired, but also to reach a higher level of sensitivity, accuracy, objectivity, and reproducibility than traditional data analysis methods.
The goal of our research is to develop advanced image processing and analysis methods to enable efficient, accurate, and reproducible quantification and characterization of cellular and molecular dynamic processes. This is accomplished by:
- Developing advanced methods for image restoration, enhancement, and super-resolution.
- Developing model-based methods for image segmentation, registration, detection, tracking, and analysis.
- Making efficient and robust implementations of the developed methods in the form of user-friendly software tools.
- Carrying out thorough evaluations of the methods by means of computer simulations and comparisons with human experts.
- Assessing the practical value of the methods by using them to answer biologically and clinically relevant research questions.
Past and current research topics include:
- Automated analysis of time-lapse fluorescence microscopy images
- Survey of methods for neuron tracing and quantification
- Survey of tracking methods in cell and developmental biology
- Level-set based cell tracking in time-lapse fluorescence microscopy
- Particle filtering for multiple object tracking in molecular cell biology
- Comparison of spot detection methods in fluorescence microscopy
- Survey of automated tracking methods for molecular bioimaging
- Neurite quantification from fluorescence microscopy images
- Comparison of super-resolution reconstruction methods in MRI
- Nonlinear diffusion for improved quantification and visualization in 3DRA
- Chronological review of interpolation techniques
- Symmetrical piecewise polynomial kernels for image interpolation
- Sinc-approximating kernels derived from classical polynomial interpolation
- Comparison of convolution-based methods for medical image interpolation
- Review of retrospective motion correction in DSA
- Fast image registration for motion correction in DSA
- Clinical evaluation of a fast motion correction technique for DSA