cranext

A deep learning model for skull reconstruction task.

https://github.com/guitared/cranext

Science Score: 67.0%

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

  • CITATION.cff file
    Found 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: ieee.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.9%) to scientific vocabulary

Keywords

cranext skull-reconstruction
Last synced: 6 months ago · JSON representation ·

Repository

A deep learning model for skull reconstruction task.

Basic Info
Statistics
  • Stars: 6
  • Watchers: 2
  • Forks: 3
  • Open Issues: 0
  • Releases: 2
Topics
cranext skull-reconstruction
Created over 1 year ago · Last pushed 8 months ago
Metadata Files
Readme Citation

README.md

CraNeXt

CraNeXt is a deep learning model for skull reconstruction tasks. The input is a binary voxel is a defective skull, and the output is a binary voxel representing a complete skull.

CraNeXt architecture

Usage Example

Open In Colab

For a detailed demonstration of how to use CraNeXt, please refer to our example.ipynb notebook. This notebook provides step-by-step instructions and code examples for:

  • Downloading sample SkullBreak dataset and preparing input data
  • Using the CraNeXt model with pretrained weights on SkullBreak
  • Running skull reconstruction and performing evaluation
  • Visualizing reconstruction result

You can run the notebook directly in Google Colab by clicking the Colab badge above or locally.

CraNeXt architecture

Requirements

Use pip to install the requirements as follows: !pip install -r requirements.txt

Citation

Please refer to our full manuscript in IEEE Access. If you use the model, you can cite it with the following bibtex.

@article {CraNeXt, author = { Kesornsri, Thathapatt and Asawalertsak, Napasara and Tantisereepatana, Natdanai and Manowongpichate, Pornnapas and Lohwongwatana, Boonrat and Puncreobutr, Chedtha and Achakulvisut, Titipat and Vateekul, Peerapon }, journal = { IEEE Access }, title = { CraNeXt: Automatic Reconstruction of Skull Implants With Skull Categorization Technique }, year = { 2024 }, volume = { 12} , pages = { 84907--84922 }, keywords = { Skull;Implants;Image reconstruction;Shape measurement;Three-dimensional displays;Computer architecture;Computational modeling;Skull reconstruction;deep learning;skull categorization;autoimplant;volumetric shape completion }, doi = { 10.1109/ACCESS.2024.3415173 }, url = { https://doi.org/10.1109/access.2024.3415173 } }

Owner

  • Name: Guitared
  • Login: guitared
  • Kind: user
  • Location: Thailand

Code for Loved

Citation (CITATION.cff)

@article{CraNeXt,
  author={Kesornsri, Thathapatt and Asawalertsak, Napasara and Tantisereepatana, Natdanai and Manowongpichate, Pornnapas and Lohwongwatana, Boonrat and Puncreobutr, Chedtha and Achakulvisut, Titipat and Vateekul, Peerapon},
  journal={IEEE Access}, 
  title={CraNeXt: Automatic Reconstruction of Skull Implants With Skull Categorization Technique}, 
  year={2024},
  volume={12},
  pages={84907-84922},
  keywords={Skull;Implants;Image reconstruction;Shape measurement;Three-dimensional displays;Computer architecture;Computational modeling;Skull reconstruction;deep learning;skull categorization;autoimplant;volumetric shape completion},
  doi={10.1109/ACCESS.2024.3415173},
  url={https://doi.org/10.1109/access.2024.3415173}
}

GitHub Events

Total
  • Watch event: 4
  • Push event: 1
  • Fork event: 1
Last Year
  • Watch event: 4
  • Push event: 1
  • Fork event: 1