Overview
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NeuroFlow: A streamlined toolkit for DWI post-processing, offering advanced analysis and visualization for neuroimaging research.
Free software: MIT license
Documentation: https://neuroflow.readthedocs.io.
Features
Estimation of tensor derivatives (FA, MD, AD, RD, etc.) using either MRtrix3 or DIPY.
Registration of numerous volumetric parcellation atlases to subjects’ native T1w and DWI images.
Estimation of numerous distribution metrices (e.g. mean, median, IQR-mean, etc.) of diffusion metrics within each parcellation unit.
Automatic extraction of available covariates originating from different sources (demographics, temporal, environmental).
Quality control of the preprocessing of the diffusion MRI data.
Usage
Basic Usage
$ neuroflow process <input_dir> <output_dir> <google_credentials>
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
Metadata
Release files for neuroflow-yalab 0.1.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| neuroflow_yalab-0.1.9.tar.gz | 36.7 MB | Without provenance | Details for neuroflow_yalab-0.1.9.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| neuroflow_yalab-0.1.9-py3-none-any.whl | Python 3 | none | any | Details for neuroflow_yalab-0.1.9-py3-none-any.whl |
Total release size: 74.3 MB
Release files / neuroflow_yalab-0.1.9.tar.gz
| Download URL | neuroflow_yalab-0.1.9.tar.gz |
|---|---|
| Size | 36.7 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/6.1.0 CPython/3.12.3
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Release files / neuroflow_yalab-0.1.9-py3-none-any.whl
| Download URL | neuroflow_yalab-0.1.9-py3-none-any.whl |
|---|---|
| Size | 37.7 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/6.1.0 CPython/3.12.3
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Security for neuroflow-yalab 0.1.9
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