TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
By Fernando Pérez-García, Rachel Sparks, Sébastien Ourselin. Comput. Methods Programs Biomed., 2020
558 citations recorded by the source corpus.
Highlights • Open-source Python library for preprocessing, augmentation and sampling of medical images for deep learning.• Support for 2D, 3D and 4D images such as X-ray, histopathology, CT, ultrasound and diffusion MRI.• Modular design inspired by the deep learning framework PyTorch.• Focus on reproducibility and traceability to encourage open-science practices.• Compatible with related frameworks for medical image processing with deep learning.
Subfields: Biophysics, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/031e3e9b8240d61a265e5434db26dfe52bd02b47
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biophysics
- Klaus Hermann Maier-Hein
- Sébastien Ourselin
- Holger R. Roth
- M. Jorge Cardoso
- Tom Kamiel Magda Vercauteren
- Andriy Myronenko
- Daguang Xu
- Wenqi Li
In Computer Vision and Pattern Recognition
- Sébastien Ourselin
- Daguang Xu
- Tom Kamiel Magda Vercauteren
- Wenqi Li
- Klaus Hermann Maier-Hein
- Dong Yang
- Holger R. Roth
- Paul F. Jaeger
In Radiology, Nuclear Medicine and Imaging
- Sébastien Ourselin
- Andriy Myronenko
- Klaus Hermann Maier-Hein
- Dong Yang
- Holger R. Roth
- M. Jorge Cardoso
- Marc Modat
- Tom Kamiel Magda Vercauteren
Citations in the corpus
- MONAI: An open-source framework for deep learning in healthcare (2022, methodology): “MONAI provides adapter tools to accommodate the use of third-party transforms from packages such as ITK [13], torchIO [17], Kornia [18], BatchGenerator [19], Rising [20], and cuCIM [21].”