NiftyNet: a deep-learning platform for medical imaging. NiftyNet is a TensorFlow-based open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. NiftyNet is a consortium of research organisations (BMEIS – School of Biomedical Engineering and Imaging Sciences, King’s College London; WEISS – Wellcome EPSRC Centre for Interventional and Surgical Sciences, UCL; CMIC – Centre for Medical Image Computing, UCL; HIG – High-dimensional Imaging Group, UCL), where BMEIS acts as the consortium lead.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Alain Jungo, Olivier Scheidegger, Mauricio Reyes, Fabian Balsiger: pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis (2020) arXiv
- Fernando Pérez-García, Rachel Sparks, Sebastien Ourselin: TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning (2020) arXiv
- Frank Mancolo: Eisen: a python package for solid deep learning (2020) arXiv