Wiki source code of 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

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85.1	3	==== This collab describes the use of the desktop version of the QUINT workflow. The integrated QUINT online service will soon be available [[here.>>https://wiki.ebrains.eu/bin/view/Collabs/quint-demo/]] ====
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72.2	6	[[image:QUINT_workflow_Plaques.png\|\|height="470" style="float:left" width="1277"]]
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	27	==== Online documentation ====
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82.1	29	[[QUINT workflow user documentation>>https://quint-workflow.readthedocs.io]]
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72.2	31	[[QuickNII user documentation>>https://quicknii.readthedocs.io/en/latest/index.html]]
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	33	[[VisuAlign user documentation>>https://visualign.readthedocs.io/en/latest/index.html]]
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83.1	35	[[Ilastik user documentation>>https://quint-workflow.readthedocs.io]]
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78.1	37	[[Nutil user documentation>>https://nutil.readthedocs.io/en/latest/index.html]]
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79.1	39	[[MeshView user documentation>>https://meshview-for-brain-atlases.readthedocs.io]]
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66.1	41	== ==
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49.1	43	== (% style="color:#c0392b" %)Description(%%) ==
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62.2	45	The QUINT workflow enables an atlas-based analysis of extracted features from histological image sections from the rodent brain by using 3D reference atlases.
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62.2	47	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.
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62.2	49	The workflow is built on the following open-access software.
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62.2	51	* [[(% style="color:#2980b9" %)//ilastik//>>doc:.3\. Image segmentation with ilastik.WebHome]](%%) allows the extraction of labelled features such as cells, by using machine-learning image segmentation.
36.2	52	* [[(% style="color:#2980b9" %)//QuickNII//>>doc:.Image registration to reference atlas using QuickNII.WebHome]](%%) generates custom-angle slices from volumetric brain atlases to match the proportions and cutting plane of histological sections.
62.2	53	* //[[(% style="color:#3498db" %)VisuAlign>>doc:.Image registration to reference atlas using QuickNII.WebHome]]//(%%) is then used for non-linear alignment of the reference-atlas slice to the section image.
36.2	54	* (% style="color:#2980b9" %)//Nutil//(%%) enables image [[transformations>>doc:.1\. Preparing the images.WebHome]], in addition to [[quantification and spatial analysis>>doc:.4\. Quantification and spatial analysis with Nutil.WebHome]] of features by drawing on the output of //ilastik// and //QuickNII//.
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62.2	56	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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76.1	58	[[[[image:Youtube_QUINT.PNG\|\|height="281" style="float:right" width="499"]]>>https://www.youtube.com/watch?v=8oeg3qTzLnE]]
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76.1	60	[[[[image:Quint tutorial video pic.png\|\|height="300" style="float:left" width="487"]]>>https://www.youtube.com/watch?v=n-gQigcGMJ0]]
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43.2	72	QUINT workflow video
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52.1	75	== (% style="color:#c0392b" %)Workflow highlights(%%) ==
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62.2	79	The semi-automated QUINT workflow uses open-access software that can be operated without any scripting knowledge.
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62.2	85	Because the quantifications are performed in regions defined by a reference atlas, the region definitions are standardised, allowing comparisons of data from different laboratories.
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	88	==== (% style="color:#c0392b" %)References(%%) ====
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57.1	90	* 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>>https://www.frontiersin.org/articles/10.3389/fninf.2019.00075/full]]
53.2	91	* 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>>https://www.frontiersin.org/articles/10.3389/fninf.2020.00037/full]]
56.1	92	* 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>>https://www.nature.com/articles/s41592-019-0582-9]]
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	94	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>>https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216796]]
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58.1	97	==== ====
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