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1 | [[image:QUINT_workflow_Plaques.png||style="float:left"]] | ||
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3 | == (% style="color:#c0392b" %)**Description**(%%) == | ||
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5 | **The QUINT workflow enables an atlas based analysis of extracted features from histological image sections from the rodent brain using 3D reference atlases. ** | ||
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7 | **Examples of use are: cell counting and spatial distributions; determination of projection areas in connectivity experiments; exploration of pathological hallmarks in brain disease models. Integration of various data to the same reference space enables new exploration strategies and re-use of experimental data.** | ||
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9 | The workflow is built on the following open access software: | ||
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11 | * [[(% style="color:#2980b9" %)//ilastik//>>doc:.3\. Image segmentation with ilastik.WebHome]](%%) allows the extraction of labelled features such as cells, using machine learning image segmentation. | ||
12 | * [[(% 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. | ||
13 | * //[[(% style="color:#3498db" %)VisuAlign>>doc:.Image registration to reference atlas using QuickNII.WebHome]]//(%%) is then used for nonlinear alignment of the reference atlas slice to the section image.. | ||
14 | * (% 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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16 | 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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18 | [[[[image:Youtube_QUINT.PNG||height="282" style="float:left" width="500"]]>>https://www.youtube.com/watch?v=8oeg3qTzLnE]] | ||
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34 | QUINT workflow video | ||
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36 | == (% style="color:#c0392b" %)**Workflow highlights**(%%) == | ||
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38 | (% class="box successmessage" %) | ||
39 | ((( | ||
40 | The semi-automated QUINT workflow uses open access software that can be operated without any scripting knowledge. | ||
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46 | 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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49 | ==== (% style="color:#c0392b" %)**References**(%%) ==== | ||
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51 | * 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]] | ||
52 | * 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]] | ||
53 | * 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>>attach:https://www.nature.com/articles/s41592-019-0582-9]] | ||
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55 | 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 | ==== (% style="color:#c0392b" %)**User support**(%%) ==== | ||
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60 | * [[Nutil>>https://github.com/Neural-Systems-at-UIO/nutil]] | ||
61 | * [[QuickNII>>https://www.nitrc.org/projects/quicknii]] | ||
62 | * [[VisuAlign>>https://www.nitrc.org/projects/visualign/]] | ||
63 | * [[ilastik>>https://www.ilastik.org/]] | ||
64 | ))) |