[A Massive Open Oneline Course (MOOC) on pratical histology: A goal, a tool, a large public ! Return on a first experience]. / Un « Massive Open Online Course ¼ (MOOC) sur des travaux pratiques en histologie : un objectif, un outil, un public varié ! Retour sur une première expérience.

A goal ! The MOOC entitled "Introduction to Histology, A Human Tissue Exploration" correspond to our vision of the practice of General Histology, which is based on the ability to diagnose 5 families of biological tissues. Ultimately, participants must be able to recognize the different types of cells and all the surrounding elements in order to understand how they organize themselves to form tissues with specific functions. A tool ! This know-how is based on reasoning from observations of microscopic structures. Learners are therefore invited to manipulate a virtual microscope to explore biological samples on histological slides digitized. Annotations, comments, drawings or photos are associated with landmarks that enrich the study of these histological sections. A target audience ! Two educational paths allow deepening the subject in a different way and thus matching the goals or motivations of each one. After a first year of experience, usage statistics and surveys of our learners show that the MOOC Histo has allowed each of them to find an interest and federate a community of motivated learners.

Collaborative analysis of multi-gigapixel imaging data using Cytomine.

MOTIVATION: Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries. RESULTS: We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications. AVAILABILITY AND IMPLEMENTATION: Cytomine (http://www.cytomine.be/) is freely available under an open-source license from http://github.com/cytomine/ A documentation wiki (http://doc.cytomine.be) and a demo server (http://demo.cytomine.be) are also available. CONTACT: info@cytomine.be SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows.

Image analysis is key to extracting quantitative information from scientific microscopy images, but the methods involved are now often so refined that they can no longer be unambiguously described by written protocols. We introduce BIAFLOWS, an open-source web tool enabling to reproducibly deploy and benchmark bioimage analysis workflows coming from any software ecosystem. A curated instance of BIAFLOWS populated with 34 image analysis workflows and 15 microscopy image datasets recapitulating common bioimage analysis problems is available online. The workflows can be launched and assessed remotely by comparing their performance visually and according to standard benchmark metrics. We illustrated these features by comparing seven nuclei segmentation workflows, including deep-learning methods. BIAFLOWS enables to benchmark and share bioimage analysis workflows, hence safeguarding research results and promoting high-quality standards in image analysis. The platform is thoroughly documented and ready to gather annotated microscopy datasets and workflows contributed by the bioimaging community.

Cytomine: Toward an Open and Collaborative Software Platform for Digital Pathology Bridged to Molecular Investigations.

PURPOSE: Digital histology is being increasingly used in research and clinical applications. In parallel, new tissue imaging methods (e.g., imaging mass spectrometry) are currently regarded as very promising approaches for better molecular diagnosis in pathology. However, these new data sources are still often underexploited because of the lack of collaborative software to share and correlate information for multimodal analysis. EXPERIMENTAL DESIGN: The open science paradigm is followed to develop new features in the web-based Cytomine software to support next-generation digital pathology bridged to molecular investigations. RESULTS: New open-source developments allow to explore whole-slide classical histology with Matrix Assisted Laser Desorption Ionisation (MALDI) imaging and to support preprocessing for biomarker discovery using laser microdissection-based microproteomics. CONCLUSIONS AND CLINICAL RELEVANCE: The updated version of Cytomine is the first open and web-based tool to enable sharing data from classical histology, molecular imaging, and cell counting for proteomics preprocessing. It holds good promise to fulfill imminent needs in molecular histopathology.