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| 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/edit/Collabs/quint-demo/WebHome]] ==== | ||
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| 6 | [[image:QUINT_workflow_Plaques.png||height="470" style="float:left" width="1277"]] | ||
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| 8 | == == | ||
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| 27 | ==== Online documentation ==== | ||
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| 29 | [[QUINT workflow user documentation>>https://quint-workflow.readthedocs.io]] | ||
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| 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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| 35 | [[Ilastik user documentation>>https://nutil.readthedocs.io/en/latest/Ilastik.html]] | ||
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| 37 | [[Nutil user documentation>>https://nutil.readthedocs.io/en/latest/index.html]] | ||
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| 39 | [[MeshView user documentation>>https://meshview-for-brain-atlases.readthedocs.io]] | ||
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| 41 | == == | ||
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| 43 | == (% style="color:#c0392b" %)**Description**(%%) == | ||
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| 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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| 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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| 49 | The workflow is built on the following open-access software. | ||
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| 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. | ||
| 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. | ||
| 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. | ||
| 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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| 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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| 58 | [[[[image:Youtube_QUINT.PNG||height="281" style="float:right" width="499"]]>>https://www.youtube.com/watch?v=8oeg3qTzLnE]] | ||
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| 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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| 72 | QUINT workflow video | ||
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| 75 | == (% style="color:#c0392b" %)**Workflow highlights**(%%) == | ||
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| 77 | (% class="box successmessage" %) | ||
| 78 | ((( | ||
| 79 | The semi-automated QUINT workflow uses open-access software that can be operated without any scripting knowledge. | ||
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| 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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| 87 | |||
| 88 | ==== (% style="color:#c0392b" %)**References**(%%) ==== | ||
| 89 | |||
| 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]] | ||
| 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]] | ||
| 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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| 97 | ==== ==== | ||
| 98 | ))) |