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

From version 63.1
edited by puchades
on 2021/10/18 09:38
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To version 8.1
edited by sharoncy
on 2020/03/09 13:53
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3 -Online documentation: - [[https:~~/~~/quicknii.readthedocs.io/en/latest/index.html>>https://quicknii.readthedocs.io/en/latest/index.html]] [[-https:~~/~~/visualign.readthedocs.io/en/latest/index.html#>>https://visualign.readthedocs.io/en/latest/index.html#]][[ -https:~~/~~/nutil.readthedocs.io/en/latest/index.html>>https://nutil.readthedocs.io/en/latest/index.html]]
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6 -Please, address your questions about our tools and workflows to [[https:~~/~~/ebrains.eu/support/>>https://ebrains.eu/support/]].
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8 -[[image:User_support_Ebrains.png]]
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11 -[[image:QUINT_workflow_Plaques.png||style="float:left"]]
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13 -== (% style="color:#c0392b" %)**Description**(%%) ==
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15 -**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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17 -**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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19 -The workflow is built on the following open-access software.
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21 -* [[(% 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.
22 -* [[(% 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.
23 -* //[[(% 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.
24 -* (% 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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26 -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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28 -[[[[image:Youtube_QUINT.PNG||height="282" style="float:left" width="500"]]>>https://www.youtube.com/watch?v=8oeg3qTzLnE]]
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44 -QUINT workflow video
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46 -== (% style="color:#c0392b" %)**Workflow highlights**(%%) ==
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50 -The semi-automated QUINT workflow uses open-access software that can be operated without any scripting knowledge.
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7 +== QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images from Rodent Brain ==
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56 -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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59 -==== (% style="color:#c0392b" %)**References**(%%) ====
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19 +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. The first – ilastik - allows the extraction of labelled features such as cells by segmentation. The second – QuickNII - generates atlas maps customised to match the proportions and cutting plane of the brain sections. The third – Nutil – enables 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.
60 60  
61 -* 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]]
62 -* 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]]
63 -* 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]]
64 -* (((
65 -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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21 += What can I find here? =
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68 -==== ====
23 +* Notice how the table of contents on the right
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29 +Describe the audience of this collab.
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