QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain

Last modified by puchades on 2022/11/02 10:16

This collab describes the use of the desktop version of the QUINT workflow. The integrated QUINT online service will soon be available here.


Online documentation

QUINT workflow user documentation

QuickNII user documentation

VisuAlign user documentation

Ilastik user documentation

Nutil user documentation  

MeshView user documentation                                


The QUINT workflow enables an atlas-based analysis of extracted features from histological image sections from the rodent brain by using 3D reference atlases. 

Examples of use are cell counting and spatial distributions, determination of projection areas in connectivity experiments, and exploration of pathological hallmarks in brain-disease models. Integration of various data to the same reference space enables new exploration strategies and reuse of experimental data.

The workflow is built on the following open-access software.

  • ilastik allows the extraction of labelled features such as cells, by using machine-learning image segmentation.
  • QuickNII generates custom-angle slices from volumetric brain atlases to match the proportions and cutting plane of histological sections.
  • VisuAlign is then used for non-linear alignment of the reference-atlas slice to the section image.
  • Nutil enables image transformations, in addition to quantification and spatial analysis of features by drawing on the output of ilastik and QuickNII.

In combination, the tools facilitate semi-automated quantification, eliminating the need for more time-consuming methods such as stereological analysis with manual delineation of brain regions.


Quint tutorial video pic.png

QUINT workflow video

Workflow highlights

The semi-automated QUINT workflow uses open-access software that can be operated without any scripting knowledge.

Because the quantifications are performed in regions defined by a reference atlas, the region definitions are standardised, allowing comparisons of data from different laboratories.


  • Yates SC et al. (2019) QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain. Front. Neuroinform. 13:75. doi: 10.3389/fninf.2019.00075
  • Groeneboom NE, Yates SC, Puchades MA and Bjaalie JG (2020) Nutil: A Pre- and Post-processing Toolbox for Histological Rodent Brain Section Images. Front. Neuroinform. 14:37. doi: 10.3389/fninf.2020.00037
  • Berg S, Kutra D, Kroeger T, et al. & Kreshuk A (2019) ilastik: interactive machine learning for (bio)image analysis. Nat Methods. 16:1226-1232. doi: 10.1038/s41592-019-0582-9
  • Puchades MA et al. (2019) Spatial registration of serial microscopic brain images to three-dimensional reference atlases with the QuickNII tool. PlosOne. 14(5): e0216796. doi: 10.1371/journal.pone.0216796