GAN-MAT: Generative Adversarial Network-based Microstructural profile covariance Analysis Toolbox
GAN-MAT is a comprehensive pipeline to analyze brain microstructure using only the T1-weighted MRI.
Three main features of GAN-MAT:
1. T1w to T2w MRI synthesis
GAN-MAT synthesizes 3D T2-weighted MRI from 3D T1-weighted MRI using a conditional generative adversarial network (GAN).
2. Myelin-sensitive proxy calculation
Using the synthesized T2-weighted MRI, GAN-MAT calculates the ratio between T1- and T2-weighted MRI.
3. Microstructural profile covariance and gradient generation
The ready-to-use microstructural profile covariance (MPC) matrix, microstructural gradient, and moment features are computed.
.. toctree:: :maxdepth: 1 :caption: Contents Table/INSTALLATION Table/USAGE NOTES Table/MAIN OUTPUTS Table/REFERENCES & ACKNOWLEDGMENTS
- Yeongjun Park, MIP Lab - Sungkyunkwan University
- Bo-yong Park, CAMIN Lab - Inha University
- Mi Ji Lee, Seoul National University Hospital
- Seulki Yoo, CAMIN Lab - Inha University
- Chae Yeon Kim, CAMIN Lab - Inha University
- Jong Young Namgung, CAMIN Lab - Inha University
- Yunseo Park, CAMIN Lab - Inha University
- Hyunjin Park, MIPL - Sungkyunkwan University
- Eunjung Lee, Poderosa
- Yeodong Yun, Poderosa
- Casey Paquola, Multiscale Neuroanatomy Lab - INM-1 at Forschungzentrum Juelich
- Boris Bernhardt, MICA Lab - Montreal Neurological Institute