Abstract
The brain is the most complex organ in the body consisting of billions of neurons that are connected in a complex functional network of both long and short distance activating or inhibitory signals over long distances. Registration of anatomical features, neuronal connectivity and genetic markers into a common coordinate framework (CCF) has therefore greatly improved our understanding of the brain but also highlighted the spatial complexity and the need for high quality 3D reference maps.
In mice, Allen’s Institute of Brain Science has pioneered this effort by generating annotated average brain atlases based on Nissl staining’s and two-photon microscopy images. However, due to differences in tissue processing such atlases are not always suitable for registration of data obtained using other imaging modalities. Therefore, we developed a digital mouse brain atlas for automated analysis of intact iDISCO cleared brains scanned with light sheet fluorescence microscopy (LSFM).
The digital LSFM mouse brain atlas incorporates a variational average LSFM mouse brain image with 20 µm isotropic resolution, which was generated from LSFM autofluorescence images of 162 individual mice brains, and anatomical annotations of the brain regions. The variational LSFM mouse brain image was created through iterative multi-resolution image registration algorithm in order to avoid the bias towards a chosen reference brain and account for morphological differences between individual mouse brains.
In mice, Allen’s Institute of Brain Science has pioneered this effort by generating annotated average brain atlases based on Nissl staining’s and two-photon microscopy images. However, due to differences in tissue processing such atlases are not always suitable for registration of data obtained using other imaging modalities. Therefore, we developed a digital mouse brain atlas for automated analysis of intact iDISCO cleared brains scanned with light sheet fluorescence microscopy (LSFM).
The digital LSFM mouse brain atlas incorporates a variational average LSFM mouse brain image with 20 µm isotropic resolution, which was generated from LSFM autofluorescence images of 162 individual mice brains, and anatomical annotations of the brain regions. The variational LSFM mouse brain image was created through iterative multi-resolution image registration algorithm in order to avoid the bias towards a chosen reference brain and account for morphological differences between individual mouse brains.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2019 International Neuroinformatics Coordinating Facility |
| Publication date | 2019 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | 2019 International Neuroinformatics Coordinating Facility. Annual Congress - University of Warsaw, Department of Physics, Warsaw, Poland Duration: 1 Sep 2019 → 2 Sep 2019 |
Conference
| Conference | 2019 International Neuroinformatics Coordinating Facility. Annual Congress |
|---|---|
| Location | University of Warsaw, Department of Physics |
| Country/Territory | Poland |
| City | Warsaw |
| Period | 01/09/2019 → 02/09/2019 |