References of "Rubens, Ulysse"
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See detailBIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows
Rubens, Ulysse ULiege; Mormont, Romain ULiege; Paavolainen, Lassi et al

in Patterns (2020), 1

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 ... [more ▼]

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. [less ▲]

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See detailCytomine: towards an open and collaborative software platform for digital pathology bridged to molecular investigations
Rubens, Ulysse ULiege; Hoyoux, Renaud; Vanosmael, Laurent et al

in Proteomics. Clinical Applications (2018)

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 ... [more ▼]

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: We followed the open science paradigm to develop new features in our web-based Cytomine software to support next-generation digital pathology bridged to molecular investigations. RESULTS: Our new open-source developments allow to explore whole-slide classical histology with MALDI imaging and to support preprocessing for biomarker discovery using laser microdissection-based microproteomics. CONCLUSIONS AND CLINICAL RELEVANCE: Our 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. This article is protected by copyright. All rights reserved. [less ▲]

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