Contents

This book chapter is part of this book. The aim of this workflow is to quantify the morphology of pancreatic stem cells lying on a 2D polystyrene substrate from phase contrast microscopy images. For this purpose, the images are first processed with a Deep Learning model trained for semantic segmentation (cell/background); next, the result is refined and individual cell instances are segmented before characterizing their morphology.

This chapter is part of this book. The chapter introduces GPU-accelerated image processing in ImageJ/Fiji. The reader is expected to have some pre-existing knowledge of ImageJ Macro programming. Core concepts such as variables, for-loops, and functions are essential. The chapter provides basic guidelines for improved performance in typical image processing workflows.

This open access textbook aims at providing detailed explanations on how to design and construct image analysis workflows to successfully conduct bioimage analysis. 

The Incucyte® Base Analysis Software provides a guided interface and purpose-built tools, which include the process of acquiring, viewing, analyzing and sharing images of living cells.

 This ImageJ function automatically or interactively sets lower and upper threshold values, segmenting grayscale images into features of interest and background.

The authors present an ImageJ-based, semi-automated phagocytosis workflow to rapidly quantitate three distinct stages during the early engulfment of opsonized beads.

FluoGAN is a fluorescence image deconvolution software combining the knowledge of acquisition physical model with gan. It takes a fluctuating sequence of blurred, undersampled and noisy images of the sample of interest  fixed sample as input from wide field or confocal and returns a super resolved image.

Dataset of single molecule localisation microscopy SMLM, mainly storm, d-storm, dna-paint for now. Data are mainly the localisation positions in text files, some are associated with brightfield images. https://doi.org/10.1038/s41592-022-01659-0

Relate is a correlative software package optimised to work with EM, EDS, EBSD, & AFM data and images.  It provides the tools you need to correlate data from different microscopes, visualise multi-layered data in 2D and 3D, and conduct correlative analyses.

• Combining data from different imaging modalities (e.g. AFM, EDS & EBSD)

• Interactive display of multi-layer correlated data

• Analytical tools for metadata interrogation

• Documented workflows and processes

LIVECell is a manually annotated and expert-validated dataset of 2D phase contrast images, consisting of over 1.6 million cells from a diverse set of cell morphologies and culture densities. It is also associated with some trained models. All are published under CC BY-NC 4.0 license.

Junction Mapper is a semi-automated software (Java Desktop application) for analysing data from images of cells in close proximity to each other in monolayers. The focus of Junction Mapper is to measure the morphology of cell boundaries, define single junctions and quantify the length, area and intensity of the staining of different proteins localised at cell-cell contacts. The output are various unique parameters that assess the contacting interface between cells and up to two junctional markers.

SynActJ (Synaptic Activity in ImageJ) is an easy-to-use fully open-source workflow that enables automated image and data analysis of synaptic activity. The workflow consists of a Fiji plugin performing the automated image analysis of active synapses in time-lapse movies via an interactive seeded watershed segmentation that can be easily adjusted and applied to a dataset in batch mode. The extracted intensity traces of each synaptic bouton are automatically processed, analyzed, and plotted using an R Shiny workflow. 

SMLM is a mature but still growing field, which still lacks efficient and user-friendly analysis and visualization software platform adapted for both users and developers. We here introduce PoCA, a powerful open-source software platform dedicated to the visualization and analysis of 2D and 3D point-cloud data.

Nanotomy shares based on the ATLASTM browser-based viewer from Zeiss. This database allow to browse data set from the publications of Giepmans lab. 

The full list of data set is availble from :

nanotomy.org

Except the papers and where otherwise noted, this work is licensed under a Creative Commons Attribution 4.0 International License

Images can be downloaded but only as screenshots (saved as png).

Orthanc aims at providing a simple, yet powerful standalone DICOM server. It is designed to improve the DICOM flows in hospitals and to support research about the automated analysis of medical images. Orthanc lets its users focus on the content of the DICOM files, hiding the complexity of the DICOM format and of the DICOM protocol.

In this challenge, a full stack of electron microscopy (EM) slices will be used to train machine-learning algorithms for the purpose of automatic segmentation of neurites in 3D. This imaging technique visualizes the resulting volumes in a highly anisotropic way, i.e., the x- and y-directions have a high resolution, whereas the z-direction has a low resolution, primarily dependent on the precision of serial cutting.

The Image Data Resource (IDR) is a public repository of image datasets from published scientific studies, where the community can submit, search and access high-quality bio-image data. It is part of The BioImage Archive stores and distributes biological images that are useful to life-science researchers. Its development will provide data archiving services to the broader bioimaging database community. This includes added-value bioimaging data resources such as EMPIAR, Cell-IDR and Tissue-IDR.

The Image Data Resource (IDR) is a public repository of image datasets from published scientific studies, where the community can submit, search and access high-quality bio-image data. It is part of The BioImage Archive stores and distributes biological images that are useful to life-science researchers. Its development will provide data archiving services to the broader bioimaging database community. This includes added-value bioimaging data resources such as EMPIAR, Cell-IDR and Tissue-IDR.

EMPIAR (https://empiar.org/ or https://www.ebi.ac.uk/empiar), the Electron Microscopy Public Image Archive, is a public resource for raw images underpinning 3D cryo-EM maps and tomograms (themselves archived in EMDB). EMPIAR also accommodates 3D datasets obtained with volume EM techniques and soft and hard X-ray tomography.