📝 SummarXiv

Abstract

PyRadiomics-cuda is a GPU-accelerated extension of the PyRadiomics library, designed to address the computational challenges of extracting three-dimensional shape features from medical images. By offloading key geometric computations to GPU hardware it dramatically reduces processing times for large volumetric datasets. The system maintains full compatibility with the original PyRadiomics API, enabling seamless integration into existing AI workflows without code modifications. This transparent acceleration facilitates efficient, scalable radiomics analysis, supporting rapid feature extraction essential for high-throughput AI pipeline. Tests performed on a typical computational cluster, budget and home devices prove usefulness in all scenarios. PyRadiomics-cuda is implemented in Python and C/CUDA and is freely available under the BSD license at https://github.com/mis-wut/pyradiomics-CUDA Additionally PyRadiomics-cuda test suite is available at https://github.com/mis-wut/pyradiomics-cuda-data-gen. It provides detailed handbook and sample scripts suited for different kinds of workflows plus detailed installation instructions. The dataset used for testing is available at Kaggle https://www.kaggle.com/datasets/sabahesaraki/kidney-tumor-segmentation-challengekits-19