LP-CNN

Kuo-Wei Lai, Manisha Aggarwal, Peter van Zijl, Xu Li & Jeremias Sulam, 2020. Learned Proximal Networks for Quantitative Susceptibility Mapping

Setup LP-CNN for SEPIA

  1. Download LP-CNN from GitHub
  2. If you haven’t setup LP-CNN in python, following the instruction in https://github.com/Sulam-Group/LPCNN, to create conda environment (see Section Environment Settings in their GitHub page)
  3. Specify the full path to LP-CNN code as ‘LPCNN_HOME’ in setup_LPCNN_environment.m in SEPIA_HOME/addons/qsm/LPCNN/
  4. Specify the full path of the Python interpreter that has LP-CNN installed as ‘python_interpreter’ in setup_LPCNN_environment.m

Your setup_LPCNN_environment.m should look something like this:

../../_images/LPCNN_setup.png

Warning

The support this method is still in an early stage and only tested on a Linux machine.

LP-CNN panel

There is no algorithm parameter needed to be adjusted with this tool at the moment.

../../_images/LPCNN.png