This repository contains methods for analyzing and quantifying neuroanatomy in X-ray microtomography images. You can find further details about how we apply the methods in this repo to analyze mm-scale brain volumes in the following paper:
Dyer, Eva L., et al. "Quantifying mesoscale neuroanatomy using X-ray microtomography." arXiv preprint, arXiv:1604.03629 (2016).
If you use any of the code or datasets in this repo, please cite this paper. Please direct any questions to Eva Dyer at edyer{at}northwestern{dot}edu.
- Code: MATLAB and Python code for running various segmentation and analysis routines.
- Data: Training and test volumes used to optimize and evaluate our methods.
- Library: Ilastik classifier files + LONI Pipeline files used to execute our distributed workflow on full data volumes (~100 GB of raw data).
- Results: Some results from running xbrain on large datasets.