Data

Tools

Indexes

Applications

Experiments

Open Source Science

brainsimulator

Brain simulation using KDE or MVN distribution

https://github.com/sipba/brainsimulator

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.4%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Brain simulation using KDE or MVN distribution

Basic Info
Statistics
  • Stars: 0
  • Watchers: 3
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 9 years ago · Last pushed over 8 years ago
Metadata Files
Readme License

README.md

brainSimulator

DOI

Functional brain image synthesis using the KDE or MVN distribution. Currently in beta. Python code. Find the documentation at http://brainsimulator.readthedocs.io/

brainSimulator is a brain image synthesis procedure for data augmentation and standardization of evaluation of ML neuroimaging pipelines. It intends to generate a new image set that share characteristics given an original one. The system focuses on nuclear imaging modalities such as PET or SPECT brain images. It analyses the dataset by applying PCA to the original dataset, and then model the distribution of samples in the projected eigenbrain space using a Probability Density Function (PDF) estimator. Once the model has been built, anyone can generate new coordinates on the eigenbrain space belonging to the same class, which can be then projected back to the image space.

Use

First of all, install the package via pypi with: pip install brainsimulator

With the new version, the whole interface has been switched to an object. This allows to train the model once and then perform as many sample drawings as required. ```python

navigate to the folder where simulator.py is located

import brainSimulator as sim

simulator = sim.BrainSimulator(algorithm='PCA', method='mvnormal') simulator.fit(originaldataset, labels) images, classes = simulator.generateDataset(originaldataset, labels, N=200, classes=[0, 1, 2]) ```

Cite

F.J. Martinez-Murcia et al (2017). "Functional Brain Imaging Synthesis Based on Image Decomposition and Kernel Modelling: Application to Neurodegenerative Diseases." Frontiers in neuroinformatics (online). DOI: 10.3389/fninf.2017.00065

Safeguards

As in the paper, it is best to use MVN modelling, but it is fundamental to test the number of components (L) used in the modelling, otherwise it will lead to overfitting. The KDE modelling works better `out of the box', but the results may be more disperse.

License

This code is released under the license GPL-3.0+.

Owner

  • Name: SiPBA
  • Login: SiPBA
  • Kind: organization
  • Email: sipba@ugr.es
  • Location: Granada, Spain

Signal Processing and Biomedical Applications research group

GitHub Events

Total
Last Year

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 37
  • Total Committers: 1
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Francisco J. Martínez p****s@g****m 37

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 19 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 4
  • Total maintainers: 1
pypi.org: brainsimulator

Nuclear brain imaging synthesis with python

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 19 Last month
Rankings
Dependent packages count: 10.0%
Forks count: 22.6%
Downloads: 32.0%
Average: 34.2%
Stargazers count: 38.8%
Dependent repos count: 67.6%
Maintainers (1)
pakitochus
Last synced: 11 months ago

Dependencies

requirements.txt pypi
  • Numpy >=1.9
  • Scikit-learn >=0.17
  • Scipy >=0.17
setup.py pypi
  • numpy *
  • scikit-learn *
  • scipy *