Software and pipelines for registration and analyses of rodent brain image data in reference atlas space

Advancements in methodologies for efficient large-scale acquisition of high-resolution serial microscopy image data have opened new possibilities for experimental studies of cellular and subcellular features across whole brains in animal models. There is a high demand for open-source software and workflows for automated or semi-automated analysis of such data, facilitating anatomical, functional, and molecular mapping in healthy and diseased brains. These studies share a common need to consistently identify, visualize, and quantify the location of observations within anatomically defined regions, ensuring reproducible interpretation of anatomical locations, and thereby allowing meaningful comparisons of results across multiple independent studies. Addressing this need, we have developed a suite of desktop and web-applications for registration of serial brain section images to three-dimensional brain reference atlases (QuickNII, VisuAlign, WebAlign, WebWarp, and DeepSlice) and for performing data analysis in a spatial context provided by an atlas (Nutil, QCAlign, SeriesZoom, LocaliZoom, and MeshView). The software can be utilized in various combinations, creating customized analytical pipelines suited to specific research needs. The web-applications are integrated in the EBRAINS research infrastructure and coupled to the EBRAINS data platform, establishing the foundation for an online analytical workbench. We here present our software ecosystem, exemplify its use by the research community, and discuss possible directions for future developments.

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Publication Details

Journal
Frontiers in Neuroinformatics
Published
2025-09-24
DOI
https://doi.org/10.3389/fninf.2025.1629388
Citations
1
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.63

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article

Software and pipelines for registration and analyses of rodent brain image data in reference atlas space

Sharon C. Yates, Trygve B. Leergaard, Jan G. Bjaalie, Gergely Csucs et al.
1 citations
Frontiers in Neuroinformatics
Cell Image Analysis Techniques
1.63
article

Software and pipelines for registration and analyses of rodent brain image data in reference atlas space

Sharon C. Yates, Trygve B. Leergaard, Jan G. Bjaalie, Gergely Csucs, Maja Puchades, Harry Carey, Arda Balkir
article en
1 citations

Abstract

Advancements in methodologies for efficient large-scale acquisition of high-resolution serial microscopy image data have opened new possibilities for experimental studies of cellular and subcellular features across whole brains in animal models. There is a high demand for open-source software and workflows for automated or semi-automated analysis of such data, facilitating anatomical, functional, and molecular mapping in healthy and diseased brains. These studies share a common need to consistently identify, visualize, and quantify the location of observations within anatomically defined regions, ensuring reproducible interpretation of anatomical locations, and thereby allowing meaningful comparisons of results across multiple independent studies. Addressing this need, we have developed a suite of desktop and web-applications for registration of serial brain section images to three-dimensional brain reference atlases (QuickNII, VisuAlign, WebAlign, WebWarp, and DeepSlice) and for performing data analysis in a spatial context provided by an atlas (Nutil, QCAlign, SeriesZoom, LocaliZoom, and MeshView). The software can be utilized in various combinations, creating customized analytical pipelines suited to specific research needs. The web-applications are integrated in the EBRAINS research infrastructure and coupled to the EBRAINS data platform, establishing the foundation for an online analytical workbench. We here present our software ecosystem, exemplify its use by the research community, and discuss possible directions for future developments.

Frontiers in NeuroinformaticsVol. 19
University of Oslo (NO)
European Commission, Norges Forskningsråd, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 12%
Cell Image Analysis Techniques
1.63
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