TorchIO swMATH ID: 32330 Software Authors: Fernando Pérez-García, Rachel Sparks, Sebastien Ourselin Description: TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning. We present TorchIO, an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images for deep learning. It follows the design of PyTorch and relies on standard medical image processing libraries such as SimpleITK or NiBabel to efficiently process large 3D images during the training of convolutional neural networks. We provide multiple generic as well as magnetic-resonance-imaging-specific operations for preprocessing and augmentation of medical images. TorchIO is an open-source project with code, comprehensive examples and extensive documentation shared at https://github.com/fepegar/torchio Homepage: http://torchio.rtfd.io Source Code: https://github.com/fepegar/torchio Dependencies: Python Keywords: medical images; deep learning; arXiv_eess.IV; Artificial Intelligence; arXiv_cs.AI; arXiv_cs.CV; Machine Learning; arXiv_cs.LG; arXiv_stat.ML; Python Related Software: PyTorch; Python; TensorFlow; DLTK; NiftyNet; ImageNet; batchgenerators; medicaltorch; Kornia; Scikit; SciPy; SimpleITK; Mimicry; TF-GAN; pygan; Imaginaire; Keras-GAN; Keras; RadImageNet; nnDetection Cited in: 0 Publications Standard Articles 1 Publication describing the Software Year TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning Fernando Pérez-García, Rachel Sparks, Sebastien Ourselin 2020