Skip to main content

FIND Viewer: FMRI Interactive Navigation and Discovery Viewer

Project description

findviz-logo

FINDVIZ: FMRI Interactive Navigation and Discovery Viewer

Background

FINDVIZ is a browser-based visualization tool for visual exploration of fMRI data with a focus on pattern discovery. It supports the visualization of NIFTI, GIFTI, and CIFTI file formats, and time series data. Visualizations are produced using PlotlyJS.

Installation

Using pip

pip install findviz

Quick Start

To launch the application and upload an fMRI dataset through the web interface, run the following command in your terminal:

findviz

This will launch the application in your default browser. FINDVIZ was tested on Google Chrome (v134). We recommend using Chrome for the best experience.

Command Line Interface

FINDVIZ also supports uploading fMRI data from the command line:

# Launch with NIFTI files
findviz --nifti-func func.nii.gz --nifti-anat anat.nii.gz

# Launch with GIFTI files
findviz --gifti-left-func left.func.gii --gifti-right-func right.func.gii --gifti-left-mesh left.surf.gii --gifti-right-mesh right.surf.gii

# Launch with CIFTI files
findviz --cifti-dtseries data.dtseries.nii --cifti-left-mesh left.surf.gii --cifti-right-mesh right.surf.gii

# Add time series data
findviz --nifti-func func.nii.gz --timeseries timeseries1.csv timeseries2.csv

Features

  • Multi-format Support: Visualize NIFTI, GIFTI, and CIFTI neuroimaging data
  • Interactive Visualization: Explore nifti data with orthogonal and montage views, and GIFTI and CIFTI data with 3D surface views
  • Time Series Visualization: Visualize synchronized physiological, experimental design, and other time series data.
  • Preprocessing Tools: Apply normalization, filtering, detrending, and smoothing
  • Analysis Tools: Analysis functions for facilitating fMRI exploration and discovery
  • Customizable Display: Adjust colormaps, thresholds, and visualization parameters
  • State Management: Save and load visualization states

Data Formats

FINDVIZ supports the following neuroimaging data formats:

  • NIFTI (.nii, .nii.gz): 3D and 4D functional and anatomical brain images
  • GIFTI (.gii): Surface-based brain data for left and right hemispheres
  • CIFTI (.dtseries.nii): Combined surface and volume data
  • Time Series (.csv, .txt): Custom time course data for visualization alongside fMRI data
  • Task Design (.csv, .tsv): Experimental design matrices for visualization alongside fMRI data

Documentation

Coming soon!

Limitations

  • FINDVIZ displays fMRI data in voxel coordinates, and does not support the overlay of images with different spatial resolutions, even in the same coordinate space (e.g. MNI152). Thus, anatomical and/or functional images should be resampled to the same resolution before uploading.

  • FINDVIZ is not a preprocessing tool. Preprocessing options are limited to options that faciliate visualization, including normalization, detrending, smoothing, and temporal filtering. For end-to-end preprocessing, we recommend using more comprehensive tools such as FMRIPREP.

Requirements

  • Python 3.10+
  • Flask 3.0.3+
  • Matplotlib 3.9.2+
  • Nilearn 0.10.4+
  • Plotly 5.23.0+

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use FINDVIZ in your research, please cite:

Bolt, T. (2025). FINDVIZ: FMRI Interactive Navigation and Discovery Viewer. 
https://github.com/tsb46/fmri-findviz

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

findviz-0.1.4.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

findviz-0.1.4-py3-none-any.whl (2.4 MB view details)

Uploaded Python 3

File details

Details for the file findviz-0.1.4.tar.gz.

File metadata

  • Download URL: findviz-0.1.4.tar.gz
  • Upload date:
  • Size: 2.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for findviz-0.1.4.tar.gz
Algorithm Hash digest
SHA256 92022b774b377aef3b379d3b52dbb4da1cb035966f1f23a146648cca91b5d48d
MD5 1fef488d897afa9061682c0a5fc19aba
BLAKE2b-256 2fb9433304a61f9a0d5fc537d680ee0eaf1dc7e20e88a36a440081e4e1eeddca

See more details on using hashes here.

Provenance

The following attestation bundles were made for findviz-0.1.4.tar.gz:

Publisher: publish.yml on tsb46/fmri-findviz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file findviz-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: findviz-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for findviz-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 d6aabf923966465b6de1bd6ca565c64be2c00619e92fdeee184fd5345f1c662f
MD5 2f631e0c12dfc39bd854b1b391f99677
BLAKE2b-256 1673d888944cd8e8d7032e33b0d1adf5cc9cbca2a434e4565aaefd9b73cc03c6

See more details on using hashes here.

Provenance

The following attestation bundles were made for findviz-0.1.4-py3-none-any.whl:

Publisher: publish.yml on tsb46/fmri-findviz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page