Image Processing & Data Management transversal node

The objective of the BioImage Informatics – Image Processing & Data Management transversal node is to create a general framework and a complete and integrated image analysis and IT (Information Technology) solution to address a number of challenges in biological imaging and microscopy, as well as setting up a high performance grid-computing infrastructure dedicated to massive computational and data storage demands. The FBI-Bioimage Informatics node proposes different IT frameworks to deal with the data flow from the different imaging nodes. FBI BioImage Informatics node is thus transverse, by definition.

What is BioImage Informatics?

It has been defined as the [field of ] “developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problem” [deluge of molecular and cellular microscopic images] Peng, H, Bioinformatics 2008

What is BioImage Analysis?

The task of bioimage analysis, part of bioimage informatics, is to “ enable [computers] to automatically distinguish between relevant and irrelevant image information and to recognize and model spatial or temporal patterns of interest that could confirm or refute the hypotheses underlying the given experiment through quantitative analysis.” Meijering, E et al. Nature Biotechnology , 2016


Node services:

Help yourself: Image Processing & Management Software

Open Help Desk: Ask for help!

Data Management: Plan your data management


Numbers in 2018

  • 169 User image analysis projects supported by IPDM staff
  • 2500 Self usage by users of IPDM software (download or on-line access to software)
  • 197 Users trained on image analysis software

Help yourself: Image Processing & Management Software

France BioImaging develops or supports the development of different software tools that you can download or access on-line :

  • Icy Software Platform : open source bioimaging software package that aims to provide a framework for authors to share, and others to reproduce, research once the sample hits the microscope.
  • BioImageIT: a unique open-source system integrating imaging data management and analysis, and an operational solution for handling large data sets, in line with the requirements of open science.
  • Software@Serpico: Try online through a web server a set of software running on a cluster at Inria.
  • BioEmergences: Track nuclei and membranes workflow, available as a standalone software to download or as webservice , running on the European Grid Infrastructure using OpenMole.
  • OpenImadis: Open Image Discovery (openImaDis) is an enterprise-wide image and analysis management software platform for Bio-Imaging researchers. It provides shared, secure, uniform and open access to image life cycle data and algorithms. It facilitates effective management of heterogeneous images and complex analysis workflows.
Useful Links: Bio Image Informatics Inventory List of software Tools, curated by NEUBIAS COST CA15124, network of bio image analysts.

Open Help Desk: Ask for help!

Every node of France BioImaging has experts in bioimage analysis, that will guide you for your bioImaging project with three different levels according to the level of complexity of your project:

  1.  Advice on existing Tools that will answer your question, and help in the definition of your analysis workflow and possible biases.
  2. Realisation of your tailored analysis workflow  (constructing a ready to use analysis workflow based on the combination and/or adaptation of existing Tools)
  3. Putting you in contact with the most adapted image processing and analysis R&D Partner teams if the need for a new algorithm has been identified.

For any of this levels, the entry point is  to send an email at or to join us at one of our Open Desk. The calendar of the next open desk is displayed below. For users of the infrastructure without physical access to one of node, a virtual room is open once a month, where image analysts will analyse the category to which your project belong.

Paris Centre node has regular open desk event through the Image Analysis Hub @Pasteur 

Data Management: Plan your data management

We aim to support the image life cycle from the data production to its archiving through its analysis. We do not provide by ourself resources for all the stages of the image data life cycle, but we can accompany you in identifying such resources. Data management plans are becoming an essential part of any scientific project preparation. Because of the explosion of the information content in our microscopy images, but also of their size, it is now mandatory to have a clear vision (plan) about where , when and how data will be handled at the different stages of their life.

The life cycle of image data can be simplified in the different following steps: images acquisition, image processing and analysis, sharing and publishing/archiving .

  • At the level of Image Acquisition

The important information linked to the acquisition, the biological study and the sample imaged need to be stored and associated to the images (Annotations= metadata). Annotations can also comes from metrology for example (quality check).

For this images can be stored in FBI nodes or in your own institution using image data software management system such as OMERO or OpenImadis. We recommend OMERO because of its compatibility with public archives.

Controlled vocabularies (or ontology ) should be used, even if specific to the project. In the useful link below you will find a link to help you identifying the ontology you may used.

  • At the level of Image Processing and Analysis

Use reproducible image analysis : using script, macros, or visual protocols in ICY for example are a good practice: this will allow to store and save your analysis pipeline as well as the parameters used in a light text file or xml file. Most modern software (such as ICY) also store the exact version of the plugin used.

  • Sharing your data

When you have use  an image data management software, options exist to share your data or part of your data with collaborators, without duplicating the data.

These options will also allow you to share the data with anonymous users as well, for example for the review process of your publication supported by these imaging data.

Example:, Omero Marseille, Omero Montpellier 

  • Publishing and Archiving

Most of the publisher or project funded with public money will ask you to make your supporting data permanently accessible . Several options are available:

 Note that in all these solutions you have to make sure that your data will be shared FAIRly, meaning “Findable Accessible Interoperable Reusable”  

Useful Links:

FAIR Principles and metrics:

DMP editors:

Looking for an ontology:

Looking for a public database:

Each node of FBI may propose a public archive:

Euro- Bioimaging collection:


Image Analysis Hub – Institut Pasteur

↗ Website + Info

Facility: Image Analysis Hub – Institut Pasteur

Head: Jean-Yves Tinevez
Institut Pasteur, Paris, France


The Image Analysis Hub is an open access, equal access core facility committed to offering support in image analysis. Our webpage is:

What we do.

As part of the C2RT, we strive to ensure the continuity between image acquisition and image analysis. To this end we rely on our expertise in imaging and collaborate with other facilities such as the UTechS-PBI and UTechS-UBI when pertinent. All requests involving images are considered.


Our services follow four axes:

1. Offer walk-in support and trainings for questions involving image analysis.

This activity aims at offering to users quick answers to scientific questions involving well-established pipelines, for which a commercial or published tool exists and can be used conveniently. Users can address their question to the facility during open-desk sessions or directly via one-to-one requests. Depending on the effort involved, the solution is derived and proposed onsite, or individual  trainings are scheduled. For general topics, the Hub organises regular courses and workshops, possibly involving external teachers or providers.

For instance, see below for the announcement of our open-desk, organised regularly every two week.


2. Build and deploy custom analysis tools for projects requiring special developments.

Research endeavours to address original questions, for which analysis tools might be lacking or incomplete. The Image Analysis Hub aims at creating or implementing novel tools based on existing algorithms to address these questions, using skills in image analysis and software development. More than just developing the analysis tool, this activity often involves deriving a suitable analysis methodology, for which the facility expertise in microscopy and biophysics is key. Engineers work in close collaboration with users within the framework of a scientific project over medium or long durations. For projects whose effort would extend beyond typical facility usage or involve original research work, the project may be directed to the BioImage Analysis unit after a discussion with all parts.


3. Maintain an infrastructure for autonomous image analysis. Deal with complex tool deployments.

Data volume and modern analysis techniques may call for a computing power not always present in Pasteur labs. Providing open-access workstations unlock barriers to compute-intensive tools. They also act as the central sharing points for commercial softwares, making them available to the whole campus. Finally, some specialized tools require special deployment efforts, e.g. to make such a tool able to exploit the HPC infrastructure of the Institut Pasteur.


4. Develop original and innovative software tools for image analysis, whose scope exceed user projects.

Software development and image analysis skills of the facility can be leveraged to build ambitious software tools shipping innovative technologies. These tools exceed the scope of single projects and address the unarticulated needs of the Pasteur community and their creation is part of the development activity of the facility.

Services on this Facility


Image Data Handling

R&D team

Institut Pasteur – BioImage Analysis Team

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R&D team: Institut Pasteur – BioImage Analysis Team

Head: Jean-Christophe Olivo-Marin
Institut Pasteur, Rue du Docteur Roux, Paris, France

The scientific project of the BioImage Analysis (BIA) unit is to develop image analysis and computer vision tools for the processing and quantification of multi-channel temporal 3D sequences in biological microscopy. The topics are centered about the development of new algorithms for multi-particle tracking, deformable models, mathematical imaging and spatial distribution analysis. The group has produced powerful tools for spot detection and counting in real-time imaging of virus and genes, movement and shape analysis in 3D+t microscopy and cell growth analysis. These methods and algorithms have now been regrouped under the open-source and free platform Icy (, which provides a comprehensive framework for extended reproducible research in bioimage informatics. They have been instrumental for the successful achievement of a large number of collaborative biological projects.

Services on this R&D team


Image Data Handling

R&D team

Bioimage Informatics IPDM

↗ Website ↗ Service + Info

R&D team: Bioimage Informatics IPDM

Head: Perrine Paul-Gilloteaux

Institut Curie - Pavillon Trouillet-Rossignol, Rue d'Ulm, 5e Arrondissement, France

Institut Curie is active in image databases and management. The PICT imaging facility is engaged since 2011 with the Strand Life Sci. company in the development of the CID (Curie Image Database)/iManage (supported by Paris-Centre Node). The CID is linked to the “Curie Image Data center” (2x 100Tb Storage equipment and cluster for image processing and analysis). Since December 2013 CID is open to all FBI users of the PICT, under demand and common rules of imaging platforms (web client). iManage is the commercial version (with licensing), offering support to labs, to install and adapt CID on their own microscopy, at their own sites. Plugins to access the CID from Icy (Institut Pasteur) are developed and published on the central repository of Icy. An interface to interoperate with the servers at Institut Curie is under development. Integration of software developed in collaboration with Inria-Serpico ( such as ND-SAFIR, Hullkground are now integrated in the CID for automated treatment. Institut Curie, specifically with Serpico’s Team@Inria-Rennes, also develops new algorithm solutions for dynamic events detection and classification, sub-diffraction light microscopy and CLEM approaches.

Services on this R&D team


Image Data Handling

R&D team


↗ Website ↗ Service + Info

R&D team: Inria-Curie SERPICO/STED

Head & CoHead: Charles Kervrann & Jean Salamero
Inria Rennes - Bretagne Atlantique, Avenue Général Leclerc, Rennes, France

The Serpico team provides computational methods and mathematical models to automatically extract, organize and model information present in temporal series of images as they are obtained in multidimensional light and cryo-electron microscopy. In the field of membrane traffic, Serpico addresses the following themes in close collaboration with Curie Institute: image superresolution and image denoising to preserve cell integrity (photo-toxicity vs exposure time), information extraction from images and videos in multidimensional microscopy for molecular interaction analysis, spatiotemporal modeling of molecular species and multi-scale architectures, computational simulation and modeling of membrane transport at different scales. In collaboration with UMR 144 and PICT at Institut Curie, the members of Serpico participate in several joint projects (PhD and post-doc supervision, industrial contracts…). They have proposed user-friendly algorithms for processing 3D or 4D data. Other projects are related to instrumentation in microscopy including computational aspects (SERPICO@Mobyle web service) and data management (CID iManage) on the reconstruction and enhancement of images related to subdiffraction light microscopy and multimodal approaches.

Services on this R&D team


Image Data Handling

R&D team


↗ Website + Info

R&D team: SIMS @LS2N

FBI contact in the Team: Jérôme IDIER
1 Rue de la Noë, 44300 Nantes, France

The SIMS Group (Signal, Image and Sound) develops its research in the field of statistical signal and image processing. Tackling ill-posed inverse problems such as deconvolution and diffraction tomography is one of our main fields of expertise. We also focus on computational imaging issues, relying on mathematical tools from both optimization and Bayesian simulation fields. The optimal co-design of computational imaging systems is among our growing topics of interest, with the viewpoint of information theory. In the area of fluorescence microscopy, we investigate the superresolution capacity of random illumination microscopy, in collaboration with Institut Fresnel (Marseille) and the Centre for Integrative Biology (Toulouse).

Expertise of the Team:

  • Inverse problems
  • Computational imaging
  • Machine learning
R&D team

Decision and Bayesian computation Team @Institut Pasteur

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R&D team: Decision and Bayesian computation Team @Institut Pasteur

Team Leader: Jean-Baptiste Masson
Institut Pasteur, Rue du Docteur Roux, Paris, France

The lab is focused on the algorithms and computation selected by evolution to perform biological decision-making. We address this topic with an interdisciplinary approach mixing statistical physics, Bayesian machine learning, information theory and various experimental biological setups. We are pursuing 4 research axis:

  • Probabilistic pipelines and Artificial Intelligence to probe single biomolecule random walks
  • Decision-making of biological system
  • Amortized inference in Virtual Reality: DIVA + Genuage
  • Numerical Methods for temporal networks

Expertise of the Team:

  • Probabilistic pipelines for microscopy data analysis
  • Virtual reality and augmented reality applied to visualisation and analysis
  • Bayesian Inference, amortised inference and physics-based Bayesian induction.
R&D team

Computational bioimaging and bioinformatics @iBENS

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R&D team: Computational bioimaging and bioinformatics @iBENS

Team Leader: Auguste Genovesio
Institut de Biologie de l'Ecole Normale Superieure IBENS, Rue d'Ulm, Paris, France

The team develops deep learning models and large scale image and data analysis algorithms. Applications range from basic research in developmental biology and neuroscience to drug discovery in collaboration with the pharma industry. We provide the source code of our methods with all papers we publish.

Expertise of the Team:

  • Deep learning
  • Image processing & analysis
  • Computational biology
R&D team

Data modeling and computational biology @iBENS

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R&D team: Data modeling and computational biology @iBENS

Team Leader: David Holcman

The team develops tools in modeling, simulation, data analysis in cell biology and medicine. Recent developments include new super-resolution SPTs analysis.

Expertise of the Team:

  • Modeling: biology at multiple scales.
  • Simulation: stochastic and deterministic
  • Data analysis: trajectories, EEG, electrophysiology data.