For many centuries, it has been a natural human endeavor to find out how the basic building block of everything living – the cell – looks like and works. Computers have been providing significant help in this effort for several decades.
For many centuries, it has been a natural human endeavor to find out how the basic building block of everything living – the cell – looks like and works. Computers have been providing significant help in this effort for several decades. The basic tool for the observation of cells and their life is an optical microscope. Computers help with finding objects of interest, keeping them within field of view, focusing, or optical aberration correction. Computers further carry on-line as well as off-line analysis of this image data starting from image restoration through object segmentation up to classification tasks. Finally, computers are used to create sophisticated cell models (digital phantoms of cells) covering not only the 3D structure but also the dynamics and possibly interaction of cells with their surroundings. Models are important not only for biological research but also for clinical purposes, by comparing models of healthy cells or tissues with cancerous ones, and for generation of synthetic images for algorithm testing.
The lecture will present a historical overview in this field, our own results and especially contributions to the introduction of standards (benchmarks) for the comparison of available cell image analysis algorithms. Finally, we will present a vision of integration of available partial knowledge into a credible global model of cell morphology and behavior.
Michal Kozubek is a full professor at the Faculty of Informatics, Masaryk University. He is a head of the Center for Biomedical Image Analysis, and former Dean (2011-2015). His research focuses on image processing, especially as applied in microscopy for spatiotemporal cell studies. He has stayed at and collaborated with, for instance, University of Oxford (on the development of a new microscopy technique using on-line image processing, published in Nature, 1996), University of Heidelberg (on the development of computer-controlled cell tomography, published in Micron, 2002) or University of Navarra (on the development of benchmarks for the algorithms of cell segmentation and tracking, published in Bioinformatics, 2014). Recently, he participates in the integration efforts in the frame of pan-European research infrastructure for biomedical imaging Euro-BioImaging, its Czech branch Czech-BioImaging as well as COST NEUBIAS (Network of European Bioimage Analysts). He is a member of Czechoslovak Microscopy Society, European microscopy Society and IEEE Signal Processing Society. His record on Web of Knowledge contains 80 papers, over 1400 citations and h-index of 24.
Its program consists of a one-hour lecture followed by a discussion. The lecture is based on an (internationally) exceptional or remarkable achievement of the lecturer, presented in a way which is comprehensible and interesting to a broad computer science community. The lectures is in English.
The seminar is organized by the organizational committee consisting of Roman Barták (Charles University, Faculty of Mathematics and Physics), Michal Chytil (Czech Academy of Sciences, Computer Science Institute), Pavel Kordík (Czech Tech. Univ., Faculty of Information Technologies), Jan Kybic (Czech Tech. Univ., Faculty of Electrical Engineering), Michal Pěchouček (Czech Tech. Univ., Faculty of Electrical Engineering), Jiří Sgall (Charles University, Faculty of Mathematics and Physics), Vojtěch Svátek (University of Economics, Faculty of Informatics and Statistics), Michal Šorel (Czech Academy of Sciences, Institute of Information Theory and Automation), Tomáš Werner (Czech Tech. Univ., Faculty of Electrical Engineering), and Filip Železný (Czech Tech. Univ., Faculty of Electrical Engineering)
The idea to organize this seminar emerged in discussions of the representatives of several research institutes on how to avoid the undesired fragmentation of the Czech computer science community.