- Cell count analysis
- Analysis of tract tracing connections
- Resizing, rotating and renaming large Tiff images
The QUINT workflow takes you through a series of steps developed to enable researchers to quantify and analyse labelled features in a series of histological images of rodent brain sections within a known atlas space. The QuickNII and VisuAlign software are used for precise image registration; ilastik allows efficient identification of labelled objects; finally, the Nutil tool enables quantification of features per atlas region. This combination of steps facilitates semi-automated quantification, eliminating the need for more time-consuming methods, such as stereological analysis with manual delineation of brain regions.
QUINT comprises the software QuickNII, VisuAlign, ilastik and Nutil, and allows atlas-based quantification of labelled features in serial histological images from mouse or rat brains.
QuickNII and VisuAlign are tools for spatial registration of (serial) 2D image data to 3D rodent brain atlases. A linear registration is first performed using QuickNII, then VisuAlign allows refinement of the registration using non-linear methods.
The ilastik software provides workflows for automated (supervised) identification of selected pixels and classification of objects.
Nutil enables processing of histological images from rodent brains including transformation of the size, resolution, and orientation of very large histological images. It is a central tool used in the QUINT workflow, where it quantifies features in histological images based on brain atlas maps.
Are you interested in atlas based spatial quantification? Discover the QUINT workflow and interact with us to customise the workflow for your needs: Count cells, AD plaques and quantify connectivity traces in 2D images from mice and rat. The QUINT workflow is highly flexible and has developed over time in response to users’ needs. We look forward to continuing this collaboration with the research community and welcome all requests, big and small. Post us questions directly through github or at https://ebrains.eu/support/
Berg S., Kutra D., Kroeger T., Straehle C.N., Kausler B.X., Haubold C., et al. (2019) ilastik:interactive machine learning for (bio) image analysis. Nat Methods. 16, 1226–1232. https://doi.org/10.1038/s41592-019-0582-9
Groeneboom N.E., Yates S.C., Puchades M.A. and Bjaalie J.G. (2020) Nutil: A Pre- and Post-processing Toolbox for Histological Rodent Brain Section Images. Front. Neuroinform. 14:37. https://doi.org/10.3389/fninf.2020.00037
Puchades M.A., Csucs G., Lederberger D., Leergaard T.B., and Bjaalie J.G. (2019) Spatial registration of serial microscopic brain images to three-dimensional reference atlases with the QuickNII tool. PLosONE. 14 (5): e0216796. https://doi.org/10.1371/journal.pone.0216796
Yates S.C., Groeneboom N.E., Coello C., Lichtenthaler S.F., Kuhn P.H., Demuth H.U., Hartlage-Rübsamen M., Roßner S., Leergaard T., Kreshuk A., Puchades M.A., Bjaalie JG. (2019) QUINT: Workflow for quantification and spatial analysis of features in histological images from rodent brain. Front. Neuroinform. 13, 75. https://doi.org/10.3389/fninf.2019.00075