fastrad: GPU-Native Radiomics at 25x the Speed of PyRadiomics

TL;DR: We built fastrad, a PyTorch-native Python library that extracts all 8 IBSI-standardised radiomic features from medical images 25× faster than PyRadiomics on GPU — with numerically identical ...

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fastrad: GPU-Native Radiomics at 25x the Speed of PyRadiomics

Source: DEV Community

TL;DR: We built fastrad, a PyTorch-native Python library that extracts all 8 IBSI-standardised radiomic features from medical images 25× faster than PyRadiomics on GPU — with numerically identical results. It's open-source, pip-installable, and a drop-in replacement. pip install fastrad The Problem: Radiomics is Slow Radiomics — the extraction of quantitative features from CT and MRI scans — is increasingly central to oncology research. Radiomic signatures have been used to predict treatment response, prognosis, and tumour phenotype across lung, head-and-neck, and many other cancer types. The standard tool for this is PyRadiomics, developed at Dana-Farber / Brigham and Women's Hospital. It's robust, well-validated, and widely adopted. But it has one significant limitation: it runs entirely on CPU, and it's slow. On a modern 32-thread workstation, PyRadiomics takes ~3 seconds per scan. That might sound fine — until you're processing thousands of scans for a multi-cohort clinical study,

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