https://github.com/khanlab/hippunfold

BIDS App for Hippunfold (automated hippocampal unfolding and subfield segmentation)
https://github.com/khanlab/hippunfold

deep-learning hippocampus mri python segmentation

Last synced: 7 months ago
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BIDS App for Hippunfold (automated hippocampal unfolding and subfield segmentation)

• Host: GitHub
• URL: https://github.com/khanlab/hippunfold
• Owner: khanlab
• License: mit
• Created: 2020-07-24T02:14:54.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2025-12-11T04:06:42.000Z (7 months ago)
• Last Synced: 2025-12-11T18:14:28.911Z (7 months ago)
• Topics: deep-learning, hippocampus, mri, python, segmentation
• Language: Python
• Homepage: https://hippunfold.readthedocs.io
• Size: 490 MB
• Stars: 63
• Watchers: 5
• Forks: 21
• Open Issues: 33
• Metadata Files:
  • Readme: README.md
  • Contributing: docs/contributing/contributing.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-bids - hippunfold

README

          
[![Documentation Status](https://readthedocs.org/projects/hippunfold/badge/?version=latest)](https://hippunfold.readthedocs.io/en/latest/?badge=latest)

![Docker Pulls](https://img.shields.io/docker/pulls/khanlab/hippunfold)

![Version](https://img.shields.io/github/v/tag/khanlab/hippunfold?label=version)



**Full Documentation:**  [here](https://hippunfold.readthedocs.io/en/latest/?badge=latest)

# Hippunfold

This tool aims to automatically model the topological folding structure

of the human hippocampus, and computationally unfold it.

![Hippo Fold Unfold](https://raw.githubusercontent.com//khanlab/hippunfold/master/docs/images/subfields_foldunfold.png)

This is especially useful for:

- Visualization

- Topologically-constrained intersubject registration

- Parcellation (ie. registration to an unfolded atlas)

- Morphometry (eg. thickness, surface area, curvature, and gyrification measures)

- Quantitative mapping (eg. map your qT1 MRI data to a midthickness surface; extract laminar profiles perpendicular to this surface)

## NEW: Version 1.3.x release 

Major changes include the addition of unfolded space registration to a reference atlas harmonized across seven ground-truth histology samples. This method allows shifting in unfolded space, providing even better intersubject alignment. 

*Note: this replaces the default workflow, however you can revert to the legacy workflow, disabling unfolded space registration, by setting `--atlas bigbrain` or `--no-unfolded-reg`*

Read more in our [ manuscript](https://doi.org/10.7554/eLife.88404.3)

Also the ability to specify a new **experimental** UNet model that is contrast-agnostic using [synthseg](https://github.com/BBillot/SynthSeg) and trained using more detailed segmentations. This generally produces more detailed results but has not been extensively tested yet. 

Note: Docker containers for version 1.3.x and above do not come pre-shipped with nnU-net models (and are accordingly more lightweight!) - models are downloaded automatically when running, but please see the FAQ for more information!

## Workflow

The overall workflow can be summarized in the following steps:

![Pipeline Overview](https://raw.githubusercontent.com//khanlab/hippunfold/master/docs/images/hippunfold_overview_unfoldreg.png)

For more information, see

**Full Documentation:**  [here](https://hippunfold.readthedocs.io/en/latest/?badge=latest)

## Additional tools

For plotting, mapping fMRI, DWI or other data, and manipulating surfaces, see [here](https://github.com/jordandekraker/hippunfold_toolbox)

For statistical testing (spin tests) in unfolded space, see [here](https://github.com/Bradley-Karat/Hippo_Spin_Testing)

## Publications

### HippUnfold methods paper

- DeKraker, J., Haast, R. A., Yousif, M. D., Karat, B., Lau, J. C., Köhler, S., & Khan, A. R. (2022). Automated hippocampal unfolding for morphometry and subfield segmentation with HippUnfold. Elife, 11, e77945. [link](https://doi.org/10.7554/eLife.77945)

  -  **Please cite this if you use any version of HippUnfold)**

  

### Unfolded space registration and multihist7 atlas

- DeKraker Jordan, Palomero-Gallagher Nicola, Kedo Olga, Ladbon-Bernasconi Neda, Muenzing Sascha E.A., Axer Markus, Amunts Katrin, Khan Ali R., Bernhardt Boris, Evans Alan C. (2023) Evaluation of surface-based hippocampal registration using ground-truth subfield definitions eLife 12:RP88404 [link](https://doi.org/10.7554/eLife.88404.3)

  -  **Please cite this if you use HippUnfold version >= 1.3.0)**

### Commentary on surface-based hippocampal segmentation

- DeKraker J, Köhler S, Khan AR. Surface-based hippocampal subfield segmentation. Trends Neurosci. 2021 Nov;44(11):856-863. doi: 10.1016/j.tins.2021.06.005. Epub 2021 Jul 22. PMID: 34304910. [link](https://pubmed.ncbi.nlm.nih.gov/34304910/)

### Related papers

- DeKraker J, Ferko KM, Lau JC, Köhler S, Khan AR. Unfolding the hippocampus: An intrinsic coordinate system for subfield segmentations and quantitative mapping. Neuroimage. 2018 Feb 15;167:408-418. doi: 10.1016/j.neuroimage.2017.11.054. Epub 2017 Nov 23. PMID: 29175494. [link](https://pubmed.ncbi.nlm.nih.gov/29175494/)

- DeKraker J, Lau JC, Ferko KM, Khan AR, Köhler S. Hippocampal subfields revealed through unfolding and unsupervised clustering of laminar and morphological features in 3D BigBrain. Neuroimage. 2020 Feb 1;206:116328. doi: 10.1016/j.neuroimage.2019.116328. Epub 2019 Nov 1. PMID: 31682982. [link](https://pubmed.ncbi.nlm.nih.gov/31682982/)

- Karat BG, DeKraker J, Hussain U, Köhler S, Khan AR. Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion MRI. Hum Brain Mapp. 2023 Nov;44(16):5485-5503. Epub 2023 Aug 24. PMID: 37615057; PMCID: PMC10543110.[link](https://doi.org/10.1002/hbm.26461)