High-throughput morphologic phenotyping of the mouse brain with magnetic resonance histology
G. Allan Johnson, Anjum Ali-Sharief, Alexandra Badea, Jeffrey Brandenburg, Gary Cofer, Boma Fubara, Sally Gewalt, Laurence W. Hedlund, Lucy Upchurch
NeuroImage, 37(1): 82-89, 2007. PMCID: PMC1994723
Files in This Data Supplement
Representative volume data for one C57BL/6J wild-type specimen:
- civm_sample.zip (34 MB), a ZIP archive containing T1 and T2-weighted image data, label data and metadata, along with the MBAT (Mouse BIRN Atlas Tool) viewer. The version of MBAT included here will automatically open the representative dataset upon launch.
You may also download the data and MBAT separately:- civm_sample.zip (27 MB), a ZIP archive containing image and label data.
- civm_mbat.zip (7 MB), a ZIP archive containing the MBAT application.
- civm_T1_large.zip (453 MB), a ZIP archive containing a full-resolution (512x512x1024) T1 volume in Analyze format.
CIVM makes many types of data acquired for published and yet unpublished studies available through our CIVM VoxPort application. Use of VoxPort is free. Registration is required. Register for VoxPort access now. A new browser window or tab will open.We ask that you provide contact information, and agree to give credit to the Duke Center for In Vivo Microscopy for any written or oral presentation using data from this site. Please use the following acknowledgement: Imaging data provided by the Duke Center for In Vivo Microscopy NIH/NIBIB (P41 EB015897).
Instructions: Click on a link below. A new browser window or tab will open where you will be prompted to login to CIVMVoxPort. If you do not have login credentials, follow the instructions to register for access. After you login, come back to this page and re-click on a link below to go directly to the desired page.
Note: For optimal quality, please download the following videos, and view them from your local computer.
You may browse all these datasets via the CIVMVoxPort Web portal, a browser-based tool that lets you view slices without downloading the entire dataset.
Acknowledgements
This work was has been made possible through collaboration with the Biomedical Informatics Research Network, under NIH/NCRR grants P41 RR005959 (G. A. Johnson) and U24 RR021760i (A. W. Toga).
