List of Training Materials

	identifier	Additional keywords	Author(s)	Format	Prerequisites	Topics covered	Event
Metric Reloaded: how to select and use your metrics	1892		https://metrics-reloaded.dkfz.de/committee	web		Validation, Image validation, Machine learning
image.sc Forum's recommendation list for Bioimage Analysis self-study materials	1883
Introduction to 3D Analysis with 3D ImageJ Suite	1858	3D image processing	Thomas Boudier	video tutorial		Image processing, Image analysis, Object feature extraction, Cell segmentation, Shape features	NEUBIAS Academy @Home 2020
GPU Accelerated Image Processing with CLIJ2	1857	GPU	Robert Haase	video tutorial		Image analysis, Image processing, Cell segmentation, Object feature extraction	NEUBIAS Academy @Home 2020
Image Analysis of Biological Data using CellProfiler	1856		Anna Klemm	Workshop material	To be able to follow the course you need to know basic image analysis: concept of “images are a matrix of numbers” handling of multi-channel images bit-depth segmentation by applying an global threshold “analyze particles” (connected component analysis)	High content screening, Image analysis, Object feature extraction, Cell segmentation
Mathematical morphology with morphoLibJ	1855		David Legland, Ignacio Arganda-Carreras, Philippe Andrey			Morphological operation, Watershed segmentation, Object feature extraction, Texture extraction	NEUBIAS Academy @Home 2020
Sharing and licensing material	1854	licensing, data sharing, FAIR principles		Workshop material			EMBO Workshop on Advanced Methods in Bio-image Analysis, 2021
Image analysis with Python and Napari	1853		Robert Haase, Marcelo Leomil Zoccoler	Workshop material, book		Image analysis, Image processing	Helmholtz Imaging Incubator Summer Academy – From Zero to Hero
Interactive Data Visualization 101 with Fiji & Friends	1852						HIP Summer School 2021
Parallelization and heterogeneous computing: from pure CPU to GPU-accelerated image processing	1851		Robert Haase	Workshop material, video tutorial		Image analysis, Image processing	NEUBIAS Defragmentation Training School, 2022
Fractal: A framework for processing OME-Zarr high content imaging data	1850	OME-NGFF, OME-Zarr	Joel Lüthi, Gustavo de Medeiros, Lucas Pelkmans, Prisca Liberali	Workshop material		High content screening, Image analysis
Napari: n-dimensional Python image viewer	1848	Napari, Dimensionality reduction, Python	Johannes Soltwedel			Cell segmentation, Object classification, Object feature extraction	Trends in Microscopy 2023
Tracking cells in microscopy image data	1847	Difference of Gaussian	Robert Haase	Workshop material		Cell tracking	EMBO Course on 3D Developmental Imaging 2022
https://biii.eu/bioimage-data-analysis-workflows-advanced-components-and-methods	1841
Building a Bioimage Analysis Workflow Using Deep Learning	1842		Estibaliz Gómez-de-Mariscal
GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ	1840		Daniela Vorkel, Robert Haase	Book Chapter		ImageJ Macros, Image processing
Bioimage Data Analysis Workflows - Advanced Components and Methods	1839	drosophila, fruit fly, cell migration		book		Image analysis, Machine learning, Data handling, Plotting, Python, ImageJ Macros
Microscopie image analysis on Bio Image Archive	1687			Workshop material	This course is aimed at scientists working with bioimage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bio-image analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImageArchive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive is necessary, but applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading: Nature: BioImage Archive: A call for public archives for biological image data biorxiv: ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy Nucleic Acids Research: The BioStudies database—one stop shop for all data supporting a life sciences study Nature Methods: EMPIAR: a public archive for raw electron microscopy image data Nature: Image Data Resource: a bioimage data integration and publication platform BioModelZoo	Data handling, Cell segmentation, Machine learning, Image analysis
Lecture Bio-image analysis, biostatistics, programming and machine learning for computational biology at the Biotechnology Center, TU Dresden, 2021	1677	Programming	Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden	Workshop material		Image classification
Lecture Applied Bio-image Analysis at Biotechnology Center, TU Dresden, 2020	1676		Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden	video tutorial		Image convolution
Customizing ImageJ	1675		Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden	Workshop material		ImageJ Macros	Max Planck BioImaging Core Unit Network - Advanced ImageJ Macro Course, 2021
Sharing and licensing material	1674	licensing	Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden	Workshop material		Data sharing	EMBO Practical Course on Advanced Methods in Bioimage Analysis 2021
On-the-fly image processing with Python and napari	1673		Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden	Workshop material		Interactive segmentation	Smart Microscopy Workshop at the Center for Cellular imaging at the University …
Image processing with Python	1669			Tutorial	This lesson assumes you have a working knowledge of Python and some previous exposure to the Bash shell.	Image processing
Image Analysis Training Resources	1668		Jan Eglinger, Stephan Hellfrish, Aliaksandr Halavatyi, Christian Tischer, Toby Hodges, Antonio Politi	Tutorial	None if staring from first module, otherwise prerequisites are indicated for each module.	Image segmentation, Image processing, Image convolution
Data Science in Cell Imaging (DSCI) course material	1654	High content single cell phenotypic profiling, Deep learning in microscopy, Public data repositories, data harmonization, integration and fusion, Data-modeling of live cell imaging	Assaf Zaritsky		No prior biological knowledge is required; all background will be covered in the lectures. Some background in mathematics and programming is required. Prior knowledge in machine learning and/or computer vision is highly recommended, but not necessary.	Bioimage informatics, Machine learning
Bioimage analysis with Icy	1643	protocols, Icy, automation, reproducibility	Marion Louveaux	video tutorial	Basic image analysis concepts. Target audience Early Careers: Ideally suited. Learn how to make reproducible automated bioimage analysis workflows even without programming knowledge Bioimage Analysts / Facility Staff: Very useful for teaching purposes and if you need to quickly deliver modifiable, reusable workflows to non-programming user		Recording of the webinar
Introduction to R for bioimage analysis	1581		Marion Louveaux				NEUBIAS TS10 (Luxembourg)
Deep Learning from scratch	1580		RASTI Pejman , ROUSSEAU David	video tutorial	Coding notions	Machine learning, Classification
Spatiotemporal quantification of monolayer cell migration	1554		Zaritsky Assaf	Tutorial	Bio image analysts	Collective object tracking	/neubias-ts7-0
Analysis of filopodia dynamics	1552		Urbancic Vasja, Butler Richard	Tutorial	Bio image analysts	Filament tracing, Isolated object tracking	/neubias-ts7-0
High Content Image data Screening and Analysis	1551		Molnar Csaba	Tutorial	bio image analysts	High content screening	/neubias-ts7-0
Stitch Tiles, Flat Field Correction, Quantify ProtX intensity at Nuclei	1550			Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ	Montage	/neubias-ts5
Introduction to ImageJ macros: Quantify the enrichment of NPC proteins at the nuclear envelope, relative to its cytoplasmic localisation	1549		Cordelieres Fabrice P	Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ		/neubias-ts5
Working with objects: measurements in 2D and 3D	1548		Cordelieres Fabrice P.	Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ	Spot detection, Object counting, Object detection	/neubias-ts2
Analysis of Microtubule Orientation: Tracking with ImageJ, Directionality Analysis with Matlab	1547		Miura Kota, Pengo Thomas, Noerrelykke Simon	Tutorial	Must understand basics of Matlab as in the Training Material "Introduction to Matlab"	Particle tracking	/neubias-ts1
Visualization of 3D images with Matlab	1546		Cardone Giovanni	Tutorial	Must understand basics of Matlab as in the TM "Introduction to Matlab"	Visualisation	/neubias-ts1
2D image processing and Data analysis with Matlab	1545		de Castro Aguiar Paulo, Cardone Giovanni, Lindblad Joakim	Tutorial	Must understand basics of Matlab as in the TM "Introduction to Matlab"	Image segmentation	/neubias-ts1
Introduction to Matlab	1544		de Castro Aguiar Paulo, Cardone Giovanni, Lindblad Joakim	Tutorial	Matlab, for Beginners		/neubias-ts1
From workflows to simple batch macros: Quantify intensity at the nuclear envelope.	1543		Klemm Anna		Early Carreer Investigators without previous experience with image analysis or ImageJ		/neubias-ts2
From workflows to simple batch macros: Measure Phalloidin in the nucleus area.	1542		Martins Nuno	Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ		/neubias-ts2
Recording simple macros for batch processing v2	1541		Klemm Anna	Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ	Image visualisation	/neubias-ts4
Recording simple macros for batch processing	1540		Martins Nuno	Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ	Image visualisation	/neubias-ts2
Batch ImageJ macro	1539		Helfrich Stefan	Tutorial		Montage	/neubias-ts5
Tumor Blood Vessels: 3D Tubular Network Analysis	1538		Tisher Christian, Tosi Sebastien	Tutorial	ImageJ Macros	Filament tracing, Visualisation, Fluorescence microscopy, Light-sheet microscopy	/neubias-ts1
Macro Programming in ImageJ	1537		Miura Kota	Book Chapter, Tutorial
Hands-on exercises for learning Imaris	1536		Golani Ofra, Reinat Nevo			Spot detection, Visualisation, Particle tracking, Plotting, Surface rendering
Building a workflow with CellProfiler	1535		Wahlby Carolina	Tutorial	None	Cell segmentation, Cell tracking, Spot detection	/neubias-ts2
KNIME Workflow	1534		Horn Martin				/neubias-ts3
ICY Protocols and Scripts	1533		Dufour Axexandre				/neubias-ts3
Introduction to ImarisXT using MATLAB	1532		Beati Igor	Tutorial	Bio Image Analysts	Spot detection	/neubias-ts3
ImageJ2 Ops Scripting	1531		Rueden Curtis	Tutorial	Bio Image Analysts		/neubias-ts3
Developing for ImageJ and Friends	1530		Tinevez Jean-Yves		Bio Image Analysts		/neubias-ts3
Big Data & 3D Visualization	1529		Jug Florian, Pietzsch Tobias			Visualisation, Data handling	/neubias-ts7-0
Deconstructing co-localisation workflows: from co-expression assessment to super-resolved co-distribution analysis	1528		Cordelières Fabrice P.		Bio Image Analysts	Colocalisation analysis, Object-based colocalisation, Pixel-based colocalisation	/neubias-ts7-0
Using machine learning to perform image quality control	1526		Beth Cimini			Machine learning
CellProfiler Tutorial: pixel-based classification	1525		Karhohs Kyle	Tutorial	no need for programmation	Cell segmentation, Machine learning
Introduction to Image Segmentation	1524		Arganda-Carreras Ignacio	Tutorial		Cell segmentation, Morphological operation	/neubias-ts5
Introduction to ImageJ: basic operations	1523		Martins Nuno P.				/neubias-ts4
Restoration of BioImage by Digital Filters	1522		Tosi Sébastien			Image processing	/neubias-ts3
SR-Tesseler Hands-On	1521		Levet Florian	Tutorial	Bio Image Analyst	Super-resolution microscopy	/neubias-ts3
Working with pixels: filters, morphomaths and binary operations	1520		Aguiar Paulo	Tutorial	must understand basic operations in imageJ	Morphological operation	/neubias-ts2
NEUBIAS TS11	1519
NEUBIAS TS10	1518
NEUBIAS TS9	1517
NEUBIAS TS8	1516
NEUBIAS TS7	1515
NEUBIAS TS6	1513
Neubias TS5	1512
NEUBIAS TS4	1511
NEUBIAS TS3	1510
NEUBIAS TS2	1509
Assembling data for publication using FigureJ	1508		Cordelières Fabrice P.	Tutorial	must understand basic operations in imageJ	Image visualisation
Working with stacks: 3D image visualisation	1507		Cordelières Fabrice P.	Tutorial	must understand basic operations in imageJ	Visualisation
From pixels to microns	1506		Sampaio Paula	Tutorial	must understand basic operations in imageJ	Image analysis
Working with color images and images in color	1505		Sampaio Paula	Tutorial	must understand basic operations in imageJ	Image processing	/neubias-ts2
Checking and preserving the quantitative intensity content of your images	1504		Tisher Christian	Tutorial	Early Carreer Investigators without previous experience with image analysis or ImageJ	Contrast enhancement, Conversion	/neubias-ts2
Introduction to ImageJ basic operations	1503		Paul-Gilloteaux Perrine	Tutorial		Bioimage informatics	/neubias-ts2
EB1 tracking with Matlab	1502		Cardone Giovanni, de Castro Paulo, Lindblad Joakim	Tutorial		Object tracking, Particle tracking
EB1 tracking with IJ	1501		Miura Kota, Cardone Giovanni	Tutorial		Object tracking, Particle tracking
Batch_Filter_CaseStudy part 2	1499		Tosi Sébastien	Tutorial	must know basics of ImageJ/FIJI	Image processing	Event
Batch_Filter_CaseStudy part1	1498		Guiet Romain, Tosi Sébastien	Tutorial	must know basics of ImageJ/FIJI	Image processing	/neubias-ts1
Batch_Filter_CaseStudy part3 Stitch Tiles, Flat Field Correction, Quantify ProtX intensity at Nuclei	1500		Guiet Romain		must know basics of ImageJ/FIJI		/neubias-ts1
Introduction to Bio Image analysis	1497		Kota Miura	Tutorial	none	Bioimage informatics, Image analysis
Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development	1494		Jaroslav Icha, Christopher Schmied, Jaydeep Sidhaye, Pavel Tomancak, Stephan Preibisch, Caren Norden
3D object based colocalisation	1451		Fabrice Cordelières, Chong Zhang		ImageJ macro knowledge	Colocalisation analysis, Object-based colocalisation	/neubias-ts1
Image Processing and Analysis for Life Scientists MOOC	1446		Arne Seitz, Romain Guiet, Olivier Burri from BIOP EPFL		none.	Image analysis, Image processing, Light microscopy, High content screening
video tutorial on 3D vessel segmentation of synchrotron phase contrast tomography	1420	synchrotron	Tom de Vries, Chong Zhang	video tutorial		Image segmentation, Phase contrast microscopy, Contrast enhancement, Watershed segmentation
ImageJ1 - ImageJ2 transition cheat sheet	1373		Robert Haase, Kouichi C. Nakamura, Jan Eglinger, ImageJ community
Simultaneous ImageJ script and plugin development	1372		Robert Haase	Tutorial
NEUBIAS TS1	1365
Introduction to ImageJ macro language	1366		Fabrice Cordeliéres, Ofra Golani	Tutorial, Workshop material	must know basics of ImageJ/FIJI	ImageJ Macros	NEUBIAS TS1 Facility Staff School - Barcelona 2016
Kota Miura (ed) "Bioimage Data Analysis", Textbook, Wiley	45
Rafael C. Gonzalez, Richard E. Woods."Digital Image Processing", Pearson, 2008	70
Understanding the fundamental mechanisms of biofilms development and dispersal: BIAM (Biofilm Intensity and Architecture Measurement), a new tool for studying biofilms as a function of their architecture and fluorescence intensity	55
Quantitative Evaluation of Multicellular Movements in Drosophila Embryo	6