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11	11	==== ====
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14		-==== (% style="color:#c0392b" %)**Workflow Description**(%%) ====
	14	+==== (% style="color:#c0392b" %)Workflow Description(%%) ====
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16	16	The QUINT workflow enables the quantification and spatial analysis of labelled features in histological images of rodent brain sections based on reference atlases of the brain. It utilises three open-source software:
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18		-1. (% style="color:#2980b9" %)//ilastik//(%%) allows the extraction of labelled features such as cells by segmentation.
19		-1. (% style="color:#2980b9" %)//QuickNII//(%%) generates atlas maps customised to match the proportions and cutting plane of the brain sections.
20		-1. (% style="color:#2980b9" %)//Nutil//(%%) enables image transformations, in addition to quantification and spatial analysis of features by drawing on the output of ilastik and QuickNII.
	18	+1. (% style="color:#2980b9" %)//**ilastik**//(%%) allows the extraction of labelled features such as cells by segmentation.
	19	+1. (% style="color:#2980b9" %)**//QuickNII//**(%%) generates atlas maps customised to match the proportions and cutting plane of the brain sections.
	20	+1. (% style="color:#2980b9" %)**//Nutil//**(%%) enables image transformations, in addition to quantification and spatial analysis of features by drawing on the output of ilastik and QuickNII.
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22	22	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.
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25		-==== (% style="color:#c0392b" %)**Workflow highlights**(%%) ====
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27		-* The QUINT workflow is semi-automated, combining three open-source software that can be operated without scripting knowledge.
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30		-As the quantifications are performed in regions defined by a reference atlas, the region definitions are standardized, allowing comparisons of data from different laboratories.
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33		-==== (% style="color:#c0392b" %)**References**(%%) ====
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35		-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
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37		-[[https>>url:https://www.nitrc.org/projects/nutil/]][[:~~/~~/www.nitrc.org/projects/nutil>>url:https://www.nitrc.org/projects/nutil/]][[/>>url:https://www.nitrc.org/projects/nutil/]]
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39		-[[https:~~/~~/>>url:https://www.nitrc.org/projects/quicknii]][[www.nitrc.org/projects/quicknii>>url:https://www.nitrc.org/projects/quicknii]]
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41		-[[https:~~/~~/www.ilastik.org>>url:https://www.ilastik.org/]][[/>>url:https://www.ilastik.org/]]
42		-)))
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