University College London
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Registered histology, MRI, and manual annotations of over 300 brain regions in 5 human hemispheres (data from ERC Starting Grant 677697 "BUNGEE-TOOLS")

posted on 2023-10-06, 11:43 authored by Eugenio Iglesias GonzalezEugenio Iglesias Gonzalez, Adria Casamitjana, Alessia Atzeni, Benjamin Billot, David ThomasDavid Thomas, Emily BlackburnEmily Blackburn, James HughesJames Hughes, Juri Althonayan, Loic PeterLoic Peter, Matteo Mancini, Nellie RobinsonNellie Robinson, Peter Schmidt, Shauna CrampsieShauna Crampsie


This repository includes data related to the ERC Starting Grant project 677697: "Building Next-Generation Computational Tools for High Resolution Neuroimaging Studies" (BUNGEE-TOOLS). It includes: (a) Dense histological sections from five human hemispheres with manual delineations of >300 brain regions; (b) Corresponding ex vivo MRI scans; (c) Dissection photographs; (d) A spatially aligned version of the dataset; (e) A probabilistic atlas built from the hemispheres; and (f) Code to apply the atlas to automated segmentation of in vivo MRI scans.

More detailed description on what this dataset includes:

Data files and Python code for Bayesian segmentation of human brain MRI based on a next-generation, high-resolution histological atlas: "Next-Generation histological atlas for high-resolution segmentation of human brain MRI" A Casamitjana et al., in preparation.  This repository contains a set of zip files, each corresponding to one directory. Once decompressed, each directory has a readme.txt file explaining its contents.   The list of zip files / compressed directories is:  

- nifti files with summary imaging volumes of the probabilistic atlas.  

- nifti files with the blackface photographs acquired during   tissue sectioning, reconstructed into 3D volumes (in RGB).   

- jpg files with the LFB and H&E stained sections.  

- 2D nifti files with the segmentations of the histological sections.  

- ex vivo T2-weighted MRI scans and corresponding FreeSurfer processing files  

- contains the the Python code and data files that we used to segment   brain MRI scans and obtain the results presented in the article (for reproducibility purposes).   Note that it requires an installation of FreeSurfer. Also, note that the code is also maintained    in FreeSurfer (but may not produce exactly the same results):  

- photographs of the specimens prior to dissection  

- photographs of the tissue slabs prior to blocking.   

We also note that the registered images for the five cases can be found in GitHub:  

These registered images can be interactively explored with the following web interface:


ERC Starting Grant 677697


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