This repository contains the data, code, scripts and configuration files associated with the Getting Started tutorial in the QMENTA SDK documentation portal.
The tutorial helps you learn the foundations of using the QMENTA SDK and the technological ecosystem around it, including Docker and the QMENTA platform.
As a case study, the tutorial goes over the implementation of a tool that takes as inputs an oncology medical image and a segmentation mask with one or more labels, and then uses the pyradiomics library to extract radiomic features from the data. The tool will allow the user to select which classes of radiomic features they want to compute and also select a variety of image filters to be applied before extracting the radiomic features.
Pyradiomics is an open-source Python package for the extraction of radiomic features from medical images. To learn more about the aim of the project and the features of the package you can read the following publication.
Van Griethuysen, Joost JM, Andriy Fedorov, Chintan Parmar, Ahmed Hosny, Nicole Aucoin, Vivek Narayan, Regina GH Beets-Tan, Jean-Christophe Fillion-Robin, Steve Pieper, and Hugo JWL Aerts. "Computational radiomics system to decode the radiographic phenotype." Cancer research 77, no. 21 (2017): e104-e107.