Data

Tools

Indexes

Applications

Experiments

Open Source Science

bibsnet

This BIDS App provides the utility of creating a nnU-Net anatomical MRI segmentation and mask with a infant brain trained model. It can easily be included in other processing pipelines and for circumventing JLF within Nibabies.

https://github.com/dcan-labs/bibsnet

Science Score: 57.0%

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

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ✓
    Institutional organization owner
    Organization dcan-labs has institutional domain (innovation.umn.edu)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.0%) to scientific vocabulary
Last synced: 7 months ago · JSON representation

Repository

This BIDS App provides the utility of creating a nnU-Net anatomical MRI segmentation and mask with a infant brain trained model. It can easily be included in other processing pipelines and for circumventing JLF within Nibabies.

Basic Info
Statistics
  • Stars: 7
  • Watchers: 9
  • Forks: 9
  • Open Issues: 18
  • Releases: 29
Created over 4 years ago · Last pushed 7 months ago
Metadata Files
Readme License Zenodo

README.md

BIBSnet

DOI

Please visit the BIBSNet webpage for comprehensive documentation (including background information, installation and usage instructions, etc) and the BIBSNet dockerhub Repository to download the container.

We introduce BIBSNet (Baby and Infant Brain Segmentation Neural Network), an open-source, community-driven deep learning model. Provided as a BIDS App container, BIBSNet leverages data augmentation and a large, manually annotated infant dataset to produce robust and generalizable brain segmentations. The model outputs native-space brain segmentations, brain masks, and sidecar JSON files as BIDS derivatives.

BIBSnet - Stages for MRI Processing

Owner

  • Name: Developmental Cognition and Neuroimaging Labs
  • Login: DCAN-Labs
  • Kind: organization
  • Location: United States of America

Our lab uses MRI to examine typical and atypical brain development. Our research is examining children with ASD as well as children and adults with ADHD.

GitHub Events

Total
  • Create event: 8
  • Release event: 2
  • Issues event: 19
  • Watch event: 3
  • Delete event: 8
  • Issue comment event: 32
  • Push event: 63
  • Pull request review event: 1
  • Pull request event: 12
  • Fork event: 1
Last Year
  • Create event: 8
  • Release event: 2
  • Issues event: 19
  • Watch event: 3
  • Delete event: 8
  • Issue comment event: 32
  • Push event: 63
  • Pull request review event: 1
  • Pull request event: 12
  • Fork event: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 11
  • Total pull requests: 3
  • Average time to close issues: 3 months
  • Average time to close pull requests: 11 days
  • Total issue authors: 6
  • Total pull request authors: 2
  • Average comments per issue: 0.73
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 10
  • Pull requests: 3
  • Average time to close issues: 14 days
  • Average time to close pull requests: 11 days
  • Issue authors: 6
  • Pull request authors: 2
  • Average comments per issue: 0.7
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • LuciMoore (22)
  • kellyhi08 (4)
  • scott-huberty (3)
  • erikglee (3)
  • tikal004 (2)
  • dnkennedy (2)
  • lundq163 (1)
  • yanbin-niu (1)
  • moser297 (1)
  • sb8498 (1)
  • sallystoyell (1)
  • dcdeaniii (1)
  • henrycikanek (1)
  • mblesac (1)
  • pollaro (1)
Pull Request Authors
  • LuciMoore (19)
  • lundq163 (3)
  • joey-scanga (2)
  • scott-huberty (2)
  • audreymhoughton (2)
  • madisoth (2)
  • erikglee (1)
  • tikal004 (1)
  • BarryTik (1)
Top Labels
Issue Labels
enhancement (21) bug (16) question (6) documentation (3) low priority (3) good first issue (3)
Pull Request Labels
enhancement (3)

Dependencies

requirements.txt pypi
  • nibabel ==3.2.1
  • nipype ==1.7.0
  • pandas ==1.3.5
.github/workflows/docker-publish.yml actions
  • actions/checkout v3 composite
  • docker/build-push-action ac9327eae2b366085ac7f6a2d02df8aa8ead720a composite
  • docker/login-action 28218f9b04b4f3f62068d7b6ce6ca5b26e35336c composite
  • docker/metadata-action 98669ae865ea3cffbcbaa878cf57c20bbf1c6c38 composite
  • docker/setup-buildx-action 79abd3f86f79a9d68a23c75a09a9a85889262adf composite
  • sigstore/cosign-installer f3c664df7af409cb4873aa5068053ba9d61a57b6 composite
Dockerfile docker
  • ${FROM_IMAGE_NAME} latest build
rtd-requirements.txt pypi
  • mkdocs-material *