Re-occurs among tags (visualisation, rendering, viewer, classification, ...)


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. PoCA allows manipulating large datasets, and integrates a plugin architecture, a native batch analysis engine and a Python code interpreter, facilitating both the analysis of data and the integration of new methods.

Visualization, segmentation and exploration of 3D SMLM data

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.


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.

ClearMap has been designed to analyze O(TB) 3d datasets obtained via light sheet microscopy from iDISCO+ cleared tissue samples immunolabeled for proteins. The ClearMap tools may also be useful for data obtained with other types of microscopes, types of markers, clearing techniques, as well as other species, organs, or samples.

ClearMap SCreenshot

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

The basic concept is to render images (tiles) based on transformation files, without having to store the big generated image from an alignment of tiles (mosaicking).


Phindr3D is a comprehensive shallow-learning framework for automated quantitative phenotyping of three-dimensional (3D) high content screening image data using unsupervised data-driven voxel-based feature learning, which enables computationally facile classification, clustering and data visualization.

Please see our GitHub page and the original publication for details.