Institute of Information Theory and Automation

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Dr. Ing. Jan Schier

research associate
Research interests: 
bioimaging and medical imaging; image processing for microscopy; digital image processing methods; particularly image denoising and image segmentation methods; image information processing; open-source tools for bioimaging
Publications ÚTIA: 

Education and affiliation

Jan Schier received his M.Sc. degree in Technical cybernetics from the Faculty of Electrical Engineering, Czech Technical University in Prague in 1989 and his Ph.D. degree from the Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague in 1995. During his Ph.D. studies, he has joined the Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague. Recently, he has been with the Department of Image Processing.

Visiting appointments and visiting positions

Between 1995-1997 he held several short visiting appointments with the Faculty of Electrical Engineering, Mathematics and Computer Science (EWI), TU Delft, the Netherlands. In 1998-2002 he held visiting position with the SISTA/ESAT group, KU Leuven, Belgium. In both cases, he has been contributing in the field of applied signal processing (signal processing and object detection for the FMCW collision-avoidance radar, fixed-point implementation of ADSL equalization algorithms).

Curriculum Vitae

Professional activities

In 2015 and 2014, he has been program co-chair of the BIOIMAGING conference, in 2012 of the BIOINFORMATICS conference, all held with the frame of the BIOSTEC conference, organized by INSTICC, Portugal. In 2018, he has chaired the Doctoral consortium of the BIOSTEC conference.

Reviewer for the Journal of Real-Time  Image Processing (Springer) (2007-now)

Supervised bachelor project

Anna Mikeštíková, MFF UK (2022-2023) Analysis of mitotic spindle microscopy images captured with light-sheet

Dissemination activities

In the recent years, he has been supervising several secondary-school students in the frame of the Open science program of the Academy of Sciences. In 2022, in the frame of "Modern methods of digital image processing" internship, he supervises Jan Slíva, Viktor Číhal and Tadeáš Fryčák. The internship has been recently focused on processing of data from the light-sheet microscope, provided by the Institute of Animal Physiology and Genetics, using the convolutional neural networks.

You could also meet him at the UTIA stand at the Science Fair popularization event.

Outcomes of the supervision of the secondary-school students

  • His students Jiří Wolker and Maria Šimůnková have won the 2020 Student conference in the "Formal Sciences" section with their work "Spindle segmentation in big image data using convolution network DenoiSeg".
  • Jiří Wolker, under supervision of Jan Schier, has placed second in the INGENIUM category of the "Česká hlavička" competition in 2021, with his work "An interactive viewer of three-dimensional raster images". It's Czech competition rewarding talented secondary school students.
  • This viewer is, as the HyperStackView utility, displayed for public use in the Python Package Index (PyPI) repository (December 2021)
  • Jiiří Wolker has succsessfully defended his final project "Graphical application for interactive display of 3D raster images" at the "SPŠ stavební akademika Stanislava Bechyně" secondary school (57 pages, May 2022)


His conference paper "Automated counting of yeast colonies using the Fast Radial Transform algorithm", jointly authored with Bohumil Kovář, has been awarded the Best paper award at the BIOINFORMATICS 2011 conference, organized by INSTICC.



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2022-12-07 15:03

Person detail

Duration: 2018 - 2020
The goal of the project is to develop new methods for colour image acquisition and processing and to apply the results of this research in selected practical applications. The project is aimed at colour image with high colour resolution, with up to several tens colour components.
Duration: 2011 - 2014
GenEx - System for support of the FISH method evaluation The goal of this project is to develop a system for computer-aided evaluation of molecular cytogenetic analyses. The primary use of the system is in evaluation of image data originating from the FISH (Fluorescence In-Situ Hybridization) analysis.