4EU+ Quantitative Microscopy - MB100P08
Title: 4EU+ Quantitative Microscopy
Czech title: 4EU+ Kvantitativní mikroskopie
Guaranteed by: Biology Section (31-101)
Faculty: Faculty of Science
Actual: from 2023
Semester: summer
E-Credits: 6
Examination process: summer s.:
Hours per week, examination: summer s.:1/4, C+Ex [HT]
Capacity: 20
Min. number of students: unlimited
4EU+: yes
Virtual mobility / capacity: no
State of the course: taught
Language: English
Note: enabled for web enrollment
priority enrollment if the course is part of the study plan
Guarantor: Mgr. Zuzana Burdíková, Ph.D.
Teacher(s): Mgr. Zuzana Burdíková, Ph.D.
Ing. Martin Schätz, Ph.D.
Mgr. Zdeněk Švindrych, Ph.D.
Opinion survey results   Examination dates   SS schedule   
Annotation -
This course provides a comprehensive introduction to quantitative fluorescence microscopy and bioimage analysis, covering a range of advanced imaging techniques and computational tools. The curriculum is designed for students with a basic understanding of fluorescence microscopy, including sample preparation and image acquisition, as well as fundamental knowledge of programming, algorithm design, and statistics.
The course emphasizes image analysis in model studies, covering wide-field, confocal, light-sheet, and super-resolution microscopy (SIM, STORM/PALM). Students will work with various analytical software tools, including ImageJ/Fiji, Napari, Arivis Vision4D, ThunderSTORM, CLIJ, Cellpose, and Becker & Hickl FLIM software, to analyze spatial and temporal organization in biological samples. Hands-on case studies will include topics such as single-molecule localization microscopy, machine learning-based segmentation, and fluorescence lifetime imaging (FLIM).
A key component of the course is scientific data management, ensuring proper preparation of images, graphs, and tables for publication, while adhering to ethical standards in image analysis. Students will also gain experience in batch processing, automation, and quantitative analysis workflows. The course concludes with a final project, where students design a theoretical image analysis pipeline based on a chosen microscopy technique.
The course will be taught in English.
Enrolled students are expected to have basic knowledge of:
● Fluorescence microscopy (sample preparation, imaging principles).
● Image analysis concepts (pixels, resolution, bit depth, artifacts).
● Basic programming and statistics (e.g., Python, MATLAB, R, or ImageJ macros is helpful but not mandatory).
Last update: Sacherová Veronika, RNDr., Ph.D. (19.02.2025)
Requirements to the exam -

For the final assessment, students will prepare an individual project demonstrating their ability to design and describe a quantitative image analysis workflow. The project must include:

  1. Definition of a research question – Clearly state the biological problem.
  2. Selection and definition of a bioimage analysis workflow – Describe the key steps for processing and analyzing the acquired data.

Final project submission & presentation: 15.5.2025

For questions, contact: burdika@natur.cuni.cz

Last update: Sacherová Veronika, RNDr., Ph.D. (19.02.2025)
Syllabus -

The course consists of 11 sessions, held every Thursday from 14:50 to 17:55, following the schedule below:

  1. 20.2. Introduction to Image Analysis & Data Management
    1. Basics of image formation and quantitative image analysis
    2. Data management: Best practices for handling microscopy datasets
    3. Scientific visualization: Preparing images, graphs, and tables for publication
    4. Ethical considerations in image processing and publication
  2. 27.2. Deconvolution & Image Restoration (Huygens Software / Prof. Dr. Rainer Heintzmann, Institute for Physical Chemistry, Friedrich Schiller University Jena)
    1. Principles of image deconvolution
    2. Hands-on session with SVI Huygens
  3. 3. 6.3. High-Performance Image Analysis with ImageJ & CLIJ
    1. GPU-accelerated image processing using CLIJ in ImageJ
  4. 13.3. Single-Molecule Localization Microscopy (ThunderSTORM)
    1. Introduction to super-resolution microscopy (STORM/PALM)
    2. Hands-on ThunderSTORM plugin for ImageJ (case study)
  5. 20.3. Napari for Bioimage Analysis (Guest: Dr. Marcello Leomil Zoccoler, TU Dresden)
    1. Introduction to Napari: an interactive image viewer for large datasets
  6. 27.3. Lightsheet Microscopy & Arivis Vision4D
    1. Quantification & Processing of Lightsheet Microscopy Data
    2. Arivis Vision4D:
      1. Introduction & biological applications
      2. Batch processing & automation
      3. Image import, volume fusion, and 3D analysis
      4. Integration with ZEN software
  7. 3.4. Deep learning for image segmentation (Cellpose)
    1. Automated segmentation of cellular structures using Cellpose
    2. Parameter tuning and model training for biological image segmentation
  8. 10.4. Telight Lecture: Specialized session by Telight (details to be confirmed)
  9. 17.4. Fluorescence Lifetime Imaging (FLIM) for Cellular Metabolism
    1. Principles of FLIM microscopy and metabolic imaging
    2. Hands-on Becker & Hickl FLIM analysis in ImageJ (case study)
  10. 24.4. Polarization-Resolved Fluorescence Microscopy
    1. Imaging membrane protein structure & function
    2. Case study: Applications in biophysics and cell biology
  11. 15.5. Final Project Presentation & Discussion
    1. Student presentations of quantitative microscopy projects
    2. Peer discussion and feedback
Last update: Sacherová Veronika, RNDr., Ph.D. (19.02.2025)