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:

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