4EU+ Image analysis and data processing in superresolution microscopy: fairSIM and ThunderSTORM open source systems - MB100P04
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Last update: Mgr. Zuzana Burdíková, Ph.D. (19.01.2023)
to modern methodologies of super-resolution light microscopy (SIM, STORM). The priority is the practical demonstration of the image analysis software by the authors themselves. After completing the course, the participants will be able to determine what is appropriate microscopy technique used to answer the research questions, including sample preparation and data processing for publication. The course will be taught in English. Information about the course Title – Image analysis and data processing in superresolution microscopy: fairSIM and ThunderSTORM open source systems - Code – MB100P04 Guarantor – Msc. Zuzana Burdíková, Ph.D All lecturers – Msc. Zuzana Burdíková, Ph.D, Msc. Zdeněk Švindrych, Ing. Martin Schätz, Ph.D. , MSc. Ondřej Šebesta, MSc. Peter Hohoth, Ph.D., Msc. Marian Novotny, MD. Robert Haase, Ph.D., Msc. Karel Stepka Faculty, department – Faculty of Science, Laboratory of Fluorescent and Confocal Microscopy, Charles University Credits – 02 ECTS Language of instruction - English Flagship and/or transversal skills – Flagship 4, Critical thinking Capacity - 15 Examination – project Minimal requirements, prerequisites, conditions for selection, and enrolment of students: Basic knowledge of Image J is required. The course aims to explain the workflow in Image Analysis, and processing, and it is assumed that the student is interested in Image Analysis. Virtual mobility - yes How the course will be taught (one week) and the starting date –block; on august 23. -25. of the SUMMER semester of 2022, Syllabus Day 1 Introduction to superresolution microscopy: methods, principles, theoretical background image formation in Fluorescence Microscopy Resolution and Noise Super-resolution Localization Microscopy (STORM, PALM, DNA-PAINT, …) Structured Illumination Microscopy (SIM) Introduction to image processing in FIJI, ImageJ Two-channel colocalization (mitochondrial and membrane labeling) p-Value of colocalization, data filtering Quantitative analysis Quantitative data (filtering, thresholding, background separation) Filter on photon count Data visualization, 3D visualization Histogram, measurement of different parameters Pseudo-colors, pixel size, rendering mode, multicolor image Image export Image reconstruction of superresolution SIM data in ImageJ: fairSIM Super-resolved structured illumination microscopy (SR-SIM) illumination patterns SR-SIM image reconstruction algorithms, access to the plugin, and source code fairSIM, ImageJ plugin that provides SR-SIM reconstructions FairSIM reconstruction of data sets Automated reconstruction parameter estimation for data sets of adequate quality Practical part: ImageJ, fairSIM hands-on Day 2 ThunderSTORM: a comprehensive ImageJ plug-in for SMLM data analysis and super-resolution imaging https://zitmen.github.io/thunderstorm/ Single Molecule Localisation (briefly) The idea behind ThunderSTORM Workflow - localization, filtering, rendering Simulation engine 3D STORM - astigmatism method Scientific lecture Case Study Study Methods for the quantitative analyses of SMLM data, Coordinate-based colocalization / Nearest Neighbor Distance (NND) analysis in ThunderSTORM Voronoi tesselation in Coloc-Tesseler software quantitative evaluation of the spatial organization in the cell nucleus Practical Part ThunderSTORM hands-on sessions: Individual work with ThunderSTORM software Day 3 Customizing Fiji/ImageJ with ImageJ Macro, Hands-on Interactive Design of GPU-accelerated Image Data Flow Graphs in Fiji Introduction to Data Management and FAIR principles Pixel Classification Using ILASTIK Object Detection Using StarDist Practical part : ILASTIK or StarDist Hands-on |