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Software
This is a list of the software tools that I have developed together with various collaborators.
NeuralNets
NeuralNets is a PyTorch based utility library designed to quickly prototype with deep learning models for image segmentation of volumetric datasets. It offers data preprocessing and GPU accelerated augmentation, 2D/3D U-Net training and finetuning, block-based segmentation of large-scale volumes, segmentation visualization, etc.
DenoisEM
DenoisEM is a GPU accelerated, interactive ImageJ plugin that allows for fast and advanced image denoising of large-scale 3D datasets. It offers state-of-the-art algorithms, user-interactive parameter optimization, fast denoising of large-scale volumes and scalable and reproducible processing. DenoisEM is a collaborative project between the Saeys lab and Bioinformatics Core at VIB and the IPI research group.
- Project page
- Github
- Reference: Roels, J., Vernaillen, F., Kremer, A., Gonçalves, A., Aelterman, J., Luong, H. Q., Goossens, B., Philips, W., Lippens, S., & Saeys, Y. (2020). An interactive ImageJ plugin for semi-automated image denoising in electron microscopy. Nature Communications, 11(1), 1–13. https://doi.org/10.1038/s41467-020-14529-0