One of the quieter bottlenecks in medical AI pipelines is radiomic feature extraction — pulling hundreds of quantitative descriptors (texture, shape, intensity distribution) from CT and MRI scans before feeding them into classifiers, survival models, or multimodal networks. The standard tool for this is PyRadiomics. It’s robust and IBSI-compliant, but it’s CPU-only and takes ~3 seconds per scan. If you’re training on thousands of scans, or doing repeated extraction for data augmentation or delta-radiomics, that adds up fast. I built fastrad to fix this. It reimplements all 8 standardised radiomic feature classes as native PyTorch tensor operations — everything is a torch.Tensor, nothing leaves the GPU until you need it. Why it matters for ML workflows: • 25× faster end-to-end (0.116s vs 2.90s on RTX 4070 Ti) • Features stay as tensors — no numpy roundtrip before feeding your model • Numerically identical to PyRadiomics (validated to 10⁻¹¹) so pretrained models transfer • Drop-in replacement — same feature names, no pipeline rewrite needed • CPU fallback included, 2.6× faster than PyRadiomics 32-thread Feature classes covered: first-order, shape 2D/3D, GLCM, GLRLM, GLSZM, GLDM, NGTDM — the full IBSI set, not just the easy ones. This is particularly relevant if you’re working on: → Radiogenomics (combining imaging features + genomic data) → Treatment response prediction from longitudinal CTs → Multimodal models where imaging features are one branch → Any pipeline where extraction time is gating your iteration speed from fastrad import RadiomicsFeatureExtractor extractor = RadiomicsFeatureExtractor(device=“auto”) features = extractor.execute(image_path, mask_path) pip install fastrad GitHub: github.com/helloerikaaa/fastrad Pre-print: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6436486 Apache 2.0 Open to questions — especially from anyone building multimodal pipelines where fast, differentiable feature extraction would be useful. submitted by /u/helloerikaaa
Originally posted by u/helloerikaaa on r/ArtificialInteligence