GLIA

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GLioblastoma Image Analysis for integrating brain tumor growth models with medical imaging

GLIA 최신버젼 다운로드

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## GLIA
*GL*ioblastoma *I*mage *A*nalysis for calibrating brain tumor growth models is a suite of high-performance algorithms and software to integrate biophysical models of tumor growth with medical imaging data to advance personalized medicine.

GLIA  provides the following functionalities:

* 3D tumor growth simulation using complex growth models with mass effect and multiple tumor species
* Inversion algorithms for reconstructing the following parameters using a ***single*** mpMRI patient imaging scan:
  * Tumor initiation location(s) or TILs 
  * Tumor growth parameters representing cancer proliferation and infiltration
  * Tumor-induced biomechanical effects or mass effect 
  * Aggregate and localized biophysically driven imaging features
* Novel numerical schemes with parallelized execution that exploits mulitcore CPU and GPU architectures for fast solution times on medical imaging data resolutions (256x256x256)

![](https://raw.githubusercontent.com/ShashankSubramanian/GLIA/master/doc/figs/GLIA.png)

## Installation
See [installation](doc/install.md)

## Usage
See [run scripts](scripts/README.md)

## Authors
[Shashank Subramanian](mailto:shashanksubramanian@utexas.edu), Klaudius Scheufele, [George Biros](mailto:biros@oden.utexas.edu)

*Other contributors*: Naveen Himthani, Amir Gholami, Miriam Mehl, Andreas Mang

## References
If you use GLIA or contained algorithms in your research, please cite:
1. Forward tumor growth models: S. Subramanian, A. Gholami & G. Biros. **Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect**. Journal of Mathematical Biology 2019 [[arxiv](https://arxiv.org/abs/1810.05370), [jomb](https://link.springer.com/article/10.1007/s00285-019-01383-y)].

2. TIL inversion algorithms: S. Subramanian, K. Scheufele, M. Mehl & G. Biros. **Where did the tumor start? An inverse solver with sparse localization for tumor growth models**. Inverse Problems 2020 [[arxiv](https://arxiv.org/abs/1907.06564), [ip](https://iopscience.iop.org/article/10.1088/1361-6420/ab649c/meta)]; K. Scheufele, S. Subramanian & G Biros. **Fully-automatic calibration of tumor-growth models using a single mpMRI scan**. IEEE Transactions in Medical Imaging 2020 [[arxiv](https://arxiv.org/abs/2001.09173), [tmi](https://ieeexplore.ieee.org/abstract/document/9197710)].

3. Mass effect inversion algorithms: S. Subramanian, K. Scheufele, N. Himthani & G. Biros. **Multiatlas calibration of brain tumor growth models with mass effect**. MICCAI 2020 [[arxiv](https://arxiv.org/abs/2006.09932), [miccai](https://link.springer.com/chapter/10.1007/978-3-030-59713-9_53)].

## License
GLIA is distributed under GNU GENERAL PUBLIC LICENSE Version 2.
Please see [LICENSE](LICENSE.md) file. Please contact authors if any issues with the license.

GLIA

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