We have recently published the paper "Garcia-Peraza-Herrera, L. C., Fidon, L., DEttorre, C. Stoyanov, D., Vercauteren, T., Ourselin, S. (2021). Image Compositing for Segmentation of Surgical Tools without Manual Annotations. *Transactions in Medical Imaging* ([📖](https://doi.org/10.1109/TMI.2021.3057884))". Inspired by special effects, we introduce a novel deep-learning method to segment surgical instruments in endoscopic images.
We contribute to MONAI, a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem.
Open source PyTorch implementation of "Dorent, R., Booth, T., Li, W., Sudre, C. H., Kafiabadi, S., Cardoso, J., ... & Vercauteren, T. (2020). Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets. *Medical Image Analysis*, 67, 101862 ([📖](https://doi.org/10.1016/j.media.2020.101862))."
DeepReg is a freely available, community-supported open-source toolkit for research and education in medical image registration using deep learning ([📖](https://doi.org/10.21105/joss.02705)).
We provide open source code and open access data for our paper "García-Peraza-Herrera, L. C., Everson, M., Lovat, L., Wang, H. P., Wang, W. L., Haidry, R., ... & Vercauteren, T. (2020). Intrapapillary capillary loop classification in magnification endoscopy: Open dataset and baseline methodology. *International journal of computer assisted radiology and surgery*, 1-9 ([📖](https://dx.doi.org/10.1007%2Fs11548-020-02127-w))."
NiftyMIC is a Python-based open-source toolkit for research developed within the GIFT-Surg project to reconstruct an isotropic, high-resolution volume from multiple, possibly motion-corrupted, stacks of low-resolution 2D slices. Read "Ebner, M., Wang, G., Li, W., Aertsen, M., Patel, P. A., Aughwane, R., ... & David, A. L. (2020). An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. *NeuroImage*, 206, 116324 ([📖](https://doi.org/10.1016/j.neuroimage.2019.116324))."
[unmaintained] NiftyNet is a TensorFlow 1.x based open-source convolutional neural networks (CNN) platform for research in medical image analysis and image-guided therapy ([📖](https://doi.org/10.1016/j.cmpb.2018.01.0254)). It has been superseeded by [MONAI](https://github.com/Project-MONAI/MONAI/).
PUMA provides a simultaneous multi-tasking framework that takes care of managing the complexities of executing and controlling multiple threads and/or processes.
GIFT-Grab is an open-source C++ and Python API for acquiring, processing and encoding video streams in real time ([📖](http://doi.org/10.5334/jors.169)).