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[![Documentation Status](https://readthedocs.org/projects/hippunfold/badge/?version=latest)](https://hippunfold.readthedocs.io/en/latest/?badge=latest)
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![Docker Pulls](https://img.shields.io/docker/pulls/khanlab/hippunfold)
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![Version](https://img.shields.io/github/v/tag/khanlab/hippunfold?label=version)
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<img align="right" width="200" src="https://github.com/khanlab/hippunfold/assets/25106300/0c16d33e-893a-4ac3-b127-21fa843823d5">
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**Full Documentation:**  [here](https://hippunfold.readthedocs.io/en/latest/?badge=latest)
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# Hippunfold
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This tool aims to automatically model the topological folding structure
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of the human hippocampus, and computationally unfold it.
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![Hippo Fold Unfold](https://raw.githubusercontent.com//khanlab/hippunfold/master/docs/images/subfields_foldunfold.png)
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This is especially useful for:
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- Visualization
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- Topologically-constrained intersubject registration
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- Parcellation (ie. registration to an unfolded atlas)
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- Morphometry (eg. thickness, surface area, curvature, and gyrification measures)
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- Quantitative mapping (eg. map your qT1 MRI data to a midthickness surface; extract laminar profiles perpendicular to this surface)
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## NEW: Version 1.3.x release 
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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. 
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*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`*
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Read more in our [ manuscript](https://doi.org/10.7554/eLife.88404.3)
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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. 
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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!
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## Workflow
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The overall workflow can be summarized in the following steps:
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![Pipeline Overview](https://raw.githubusercontent.com//khanlab/hippunfold/master/docs/images/hippunfold_overview_unfoldreg.png)
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For more information, see
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**Full Documentation:**  [here](https://hippunfold.readthedocs.io/en/latest/?badge=latest)
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## Additional tools
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For plotting, mapping fMRI, DWI or other data, and manipulating surfaces, see [here](https://github.com/jordandekraker/hippunfold_toolbox)
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For statistical testing (spin tests) in unfolded space, see [here](https://github.com/Bradley-Karat/Hippo_Spin_Testing)
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## Publications
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### HippUnfold methods paper
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- 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)
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  -  **Please cite this if you use any version of HippUnfold)**
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### Unfolded space registration and multihist7 atlas
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- 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)
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  -  **Please cite this if you use HippUnfold version >= 1.3.0)**
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### Commentary on surface-based hippocampal segmentation
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- 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/)
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### Related papers
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- 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/)
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- 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/)
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- 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)