MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning
High content imaging of the brain holds the promise of improving our understanding of the brain’s circuitry. Here, the authors present a tool that automates the scaling and segmentation of cortical maps to accelerate neurobiological discovery using mesoscale images.
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-26255-2 |
| _version_ | 1818724733653352448 |
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| author | Dongsheng Xiao Brandon J. Forys Matthieu P. Vanni Timothy H. Murphy |
| author_facet | Dongsheng Xiao Brandon J. Forys Matthieu P. Vanni Timothy H. Murphy |
| author_sort | Dongsheng Xiao |
| collection | DOAJ |
| description | High content imaging of the brain holds the promise of improving our understanding of the brain’s circuitry. Here, the authors present a tool that automates the scaling and segmentation of cortical maps to accelerate neurobiological discovery using mesoscale images. |
| first_indexed | 2024-12-17T21:31:07Z |
| format | Article |
| id | doaj.art-fe1ae3c950c14fc1ab4f4161487e086f |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-17T21:31:07Z |
| publishDate | 2021-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-fe1ae3c950c14fc1ab4f4161487e086f2022-12-21T21:31:53ZengNature PortfolioNature Communications2041-17232021-10-0112111310.1038/s41467-021-26255-2MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learningDongsheng Xiao0Brandon J. Forys1Matthieu P. Vanni2Timothy H. Murphy3University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological ResearchUniversity of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological ResearchUniversity of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological ResearchUniversity of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological ResearchHigh content imaging of the brain holds the promise of improving our understanding of the brain’s circuitry. Here, the authors present a tool that automates the scaling and segmentation of cortical maps to accelerate neurobiological discovery using mesoscale images.https://doi.org/10.1038/s41467-021-26255-2 |
| spellingShingle | Dongsheng Xiao Brandon J. Forys Matthieu P. Vanni Timothy H. Murphy MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning Nature Communications |
| title | MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning |
| title_full | MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning |
| title_fullStr | MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning |
| title_full_unstemmed | MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning |
| title_short | MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning |
| title_sort | mesonet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning |
| url | https://doi.org/10.1038/s41467-021-26255-2 |
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