Basic Python wrapper for Plastimatch
Project description
PyPlastimatch
WORK IN PROGRESS - dummy python plastimatch wrapper and other useful functions for exploration etc.
Table of Contents
Dependencies
In order to run the code found in this repository, all the python libraries found in requirements.txt
must be installed. This can be achieved running the command:
pip3 install -r requirements.txt
In addition, you will need to download plastimatch by running:
sudo apt install plastimatch
and the DICOM for Quantitative Imaging (dcmqi) library (e.g., under Linux, download the latest release, move the content of the bin
folder under usr/local/bin
, and make the files executable).
Usage Example
Since Plastimatch and this wrapper are being used for the development of AI-base medical image analysis pipelines on the NIH CRDC Imaging Data Commons plaftorm, some examples on how to use PyPlastimatch can be found at the IDC-Examples/notebooks repository.
For instance, the "Cohort Preparation" Colab notebook contains a simple tutorial on how to get a cohort ready for any image processing applications (e.g., best practices for the conversion from DICOM to NRRD and NIfTI, pointers to pre-processing utilities).
To open the Colab notebook, click here:
Note: provided you have a Google Cloud Platform project correctly setup, you will be able to run this and all the other notebooks for free, completely on the cloud.
Further Reading
Paolo Zaffino's (un)"official" wrapper.
Further discussion about the python-wrapping of Plastimatch can be found at this discourse.slicer thread.
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