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https://github.com/cbica/nichart_viewer

Visualization tool for Neuroimaging Chart (NiChart) imaging descriptors and biomarkers

https://github.com/cbica/nichart_viewer

Science Score: 13.0%

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Keywords

nichart
Last synced: 10 months ago · JSON representation

Repository

Visualization tool for Neuroimaging Chart (NiChart) imaging descriptors and biomarkers

Basic Info
  • Host: GitHub
  • Owner: CBICA
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 47.5 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 3
Topics
nichart
Created about 3 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License

README.md

Neuroimaging Chart (NiChart) Viewer

NiChart Logo

NiChart viewer [NiChart_Viewer] is a toolbox for visualization of NiChart image descriptors and biomarkers.

Notes

The current version is primarily designed for visualizing NiChart_DLMUSE variables (regions of interest - ROIs) together with age centile curves of select ROIs derived from NiChart reference data.

Installation

You may directly install NiChart_Viewer as a package from PyPI, or build it from source.

bash conda create -n NiChart_Viewer python=3.8.8 conda activate NiChart_Viewer conda install pip pip install .

Alternatively:

bash conda create -n NiChart_Viewer python=3.8.8 conda activate NiChart_Viewer pip install NiChart_Viewer

Usage

bash NiChart_Viewer --data_file infile1.csv --data_file infile2.csv ...

Quickstart

bash cd examples/IXI_ROIs ./run_nichart_viewer_IXI.sh

The script launches the viewer using the public IXI dataset as an example (DLMUSE ROIs + demog. file with Age and Sex columns).

After launching the viewer, users can view data tables and select ROIs, correct ROIs for intra-cranial volume (ICV), merge ROI values with demographic variables (Age and Sex), view data distributions and scatter plots of variable pairs, and plot selected variables against NiChart reference centile curves

Example visualization

Disclaimer

  • The software has been designed for research purposes only and has neither been reviewed nor approved for clinical use by the Food and Drug Administration (FDA) or by any other federal/state agency.
  • By using NiChart_Viewer, the user agrees to the following license: https://www.med.upenn.edu/cbica/software-agreement-non-commercial.html

Contact

Guray Erus.

Owner

  • Name: Center for Biomedical Image Computing & Analytics (CBICA)
  • Login: CBICA
  • Kind: organization
  • Email: software@cbica.upenn.edu
  • Location: Philadelphia, PA

CBICA focuses on the development and application of advanced computation techniques.

GitHub Events

Total
Last Year

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 17 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 2
  • Total maintainers: 2
pypi.org: nichart-viewer-demo

Viewer to visualize neuroimaging chart (NiChart) image descriptors and biomarkers

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 5 Last month
Rankings
Dependent packages count: 10.6%
Average: 35.1%
Dependent repos count: 59.6%
Maintainers (1)
AlexanderGetka
Last synced: 10 months ago
pypi.org: nichart-viewer

Viewer to visualize neuroimaging chart (NiChart) image descriptors and biomarkers

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 12 Last month
Rankings
Dependent packages count: 10.8%
Average: 36.0%
Dependent repos count: 61.1%
Maintainers (2)
AlexanderGetka gaidinis
Last synced: 10 months ago

Dependencies

setup.py pypi
  • Jinja2 >=2.11.3,<3.0.0
  • MarkupSafe *
  • Pillow >=9.0.0,<10.0.0
  • PyQt5 >=5.15.4,<6.0.0
  • PyQt5_Qt5 >=5.15.2,<6.0.0
  • PyQt5_sip >=12.9.0,<13.0.0
  • Yapsy >=1.12.2,<2.0.0
  • briefcase >=0.3.5,<0.4.0
  • cycler *
  • dill >=0.3.4,<0.4.0
  • joblib *
  • matplotlib >=3.4.2,<4.0.0
  • nibabel >=3.2.1,<4.0.0
  • numpy >=1.21,<2.0.0
  • pandas ==2.0.1
  • pyparsing >=2.4.7,<3.0.0
  • pytest ==7.0.1
  • pytest-qt ==4.0.2
  • python_dateutil >=2.8.1,<3.0.0
  • pytz >=2021.1,<2022.0
  • scikit_learn >=1.0.2,<2.0.0
  • scipy >=1.6.3,<2.0.0
  • seaborn ==0.12.2
  • six >=1.16.0,<2.0.0
  • statsmodels >=0.13.0,<0.14.0
pyproject.toml pypi
requirements.txt pypi
  • Pillow >=9.0.0
  • PyQt5 >=5.15.4
  • PyQt5_Qt5 ==5.15.2
  • PyQt5_sip ==12.9.0
  • Yapsy ==1.12.2
  • cycler ==0.10.0
  • dill ==0.3.4
  • future ==0.18.2
  • joblib ==1.0.1
  • matplotlib >=3.4.2
  • nibabel ==3.2.1
  • numpy ==1.24.3
  • pandas ==2.0.1
  • poetry >=1.1.13
  • poetry_core >=1.0.7
  • pyparsing ==2.4.7
  • python_dateutil ==2.8.1
  • pytz ==2021.1
  • scikit_learn >=1.0.2
  • scipy >=1.6.3
  • seaborn ==0.12.2
  • six ==1.16.0
  • statsmodels ==0.13.0
  • wheel >=0.37.1