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pyDBT

This repository is a python extension of the DBT toolbox from LAVI-USP.

How to install?

  1. Download the toolbox or clone the directory:

    • git clone https://github.com/LAVI-USP/pyDBT.git

  2. Go to parent directory:

    • cd pyDBT

  3. Clone NVIDIA cuda-samples directory inside pyDBT:

    • git clone https://github.com/NVIDIA/cuda-samples

  4. Install the package:

    • python3 setup.py install

  5. If you have problems with arch=sm_XX, modify it in the setup.pycode according to your NVIDIA-GPU architecture. This link has some references.

  6. run the example:

    • cd pydbt && python3 example.py

  7. The toolbox was tested on Linux (Ubuntu 20) x64, and macOS BigSur (Intel) machines, with python 3.7.5.

    • You will need to install gcc for the compilation. You can install gcc 11 on macOS through homebrew.
    • Fell free to reach me if you want binaries for either Ubuntu or BigSur

  8. You can also run the MATLAB version of the toolbox.

** Please report issues here. **

Contribute?

We are pleased with any contributions. Feel free to make any pull requests or send us an e-mail.

Toolbox manual:

You can find the manual from the MATLAB version, which is pretty much the same. I will create a specific one for the python version in the future.

Contact:

If you have any questions or suggestion, please send us an e-mail:

License:

The toolbox is licensed under the GNU General Public License v3.0. Please check the licence file.

Reference:

If you use the toolbox, we will be very grateful if you refer to this paper:

Vimieiro R.B., Borges L.R., Vieira M.A.C. (2019) Open-Source Reconstruction Toolbox for Digital Breast Tomosynthesis. In: Costa-Felix R., Machado J., Alvarenga A. (eds) XXVI Brazilian Congress on Biomedical Engineering. IFMBE Proceedings, vol 70/2. Springer, Singapore.

Citations:

You can find here the papers that have used the toolbox.

Acknowledgments:

This work was supported by the São Paulo Research Foundation (FAPESP grant 2016/25750-0) and by the National Council for Scientific and Technological Development (CNPq). Nobody does anything alone, so we would like to thank the contribution of our lab members and the Barretos Love Hospital for providing the images of DBT.

Laboratory of Computer Vision (Lavi)
Department of Electrical and Computer Engineering
São Carlos School of Engineering, University of São Paulo
São Carlos - Brazil