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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.

The Cytomine cooperative host several virtual slides having an interest for pedagogical purposes or technical interest.

The main goal of the Coherent X-ray Imaging Data Bank is to create an open repository for CXI experimental data.

The Cell Image library is a large repository of images from all organisms, cell types, and processes, normal and pathological. Original format and ome-tiff format can be downloaded. 

Correlia is an open-source ImageJ/FIJI plug-in for the registration of 2D multi-modal microscopy data-sets. The software is developed at ProVIS - Centre for Correlative Microscopy and is specifically designed for the needs of chemical microscopy involving various micrographs as well as chemical maps at different resolutions and field-of-views.

The empanada-napari plugin is built to democratize deep learning image segmentation for researchers in electron microscopy (EM). It ships with MitoNet, a generalist model for the instance segmentation of mitochondria. There are also tools to quickly build and annotate training datasets, train generic panoptic segmentation models, finetune existing models, and scalably run inference on 2D or 3D data. To make segmentation model training faster and more robust, CEM pre-trained weights are used by default.

ModularImageAnalysis (MIA) is an ImageJ plugin which provides a modular framework for assembling image and object analysis workflows. Detected objects can be transformed, filtered, measured and related. Analysis workflows are batch-enabled by default, allowing easy processing of high-content datasets.

• Interact programmatically with the BioImage Archive and other data resources
• Apply pre-built machine learning models to image data
• Train and retrain machine learning models on image data
• Utilise machine learning approaches for object detection, image segmentation and de-noising
• Generate quantitative conclusions from images

ASTEC stands for Adaptive Segmentation and Tracking of Embryonic Cells. It proposes a full workflow for time lapse light sheet imaging analysis, including drift/motion compensation before the segmentation itself, and the capacity to correct for it.  It was used to process 3D+t movies acquired by the MuViSPIM light-sheet microscope in particular.

ClearMap is a toolbox for the analysis and registration of volumetric data from cleared tissues.

It was initially developed to map brain activity at cellular resolution in whole mouse brains using immediate early gene expression. It has since then been extended as a tool for the qunatification of whole mouse brain vascualtur networks at capilary resolution.

It is composed of sevral specialized modules or scripts: tubemap, cellmap, WobblyStitcher.

BaSiC is a software tool for Background and Shading correction of Optical Microscopy Images. It implements an image correction method based on low-rank and sparse decomposition to solve both shading in space and background variation in time. It can correct temporal drift in time-lapse microscopy data and thus improve continuous single-cell quantification. BaSiC is available as a Fiji/ImageJ plugin.

Voxelytic-Align is a commercial software provided as a service on cloud targetted to electron microscopy reconstruction (alignement, artifact correction...)

Hot-Knife is a library specifically designed for FIB-SEM data and thick sections, which includes code for flattening, deformable alignment with features and a more robust kind of block-matching, and some visualization, manual correction, and import and export tools (n5).

A collection of Java tools and HTTP services (APIs) for rendering transformed image tiles that includes: