Published January 23, 2023
| Version 1
Dataset
Open
FINTA/CINTA/GESTA/FIESTA Datasets
Contributors
Contact persons:
- 1. Université de Sherbrooke
Description
FINTA/CINTA/GESTA/FIESTA datasets and neural network weights
Files
degree.json
Files
(74.1 GB)
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Additional details
Related works
- Is cited by
- Preprint: 10.48550/arXiv.2212.00143 (DOI)
- Is supplement to
- Journal article: 10.1016/j.media.2021.102126 (DOI)
- Conference paper: 10.1007/978-3-031-21206-2_11 (DOI)
- Preprint: 10.48550/arXiv.2204.10891 (DOI)
References
- J. H. Legarreta, L. Petit, P.-M. Jodoin, and M. Descoteaux, "Generative sampling in tractography using autoencoders (GESTA)," Apr. 2022. https://arxiv.org/abs/2204.10891
- F. Dumais et al., "FIESTA: Autoencoders for accurate fiber segmentation in tractography," Dec. 2022. https://arxiv.org/abs/2212.00143
- J. H. Legarreta et al., "Filtering in tractography using autoencoders (FINTA)," Medical Image Analysis, vol. 72, p. 102126, Aug. 2021, doi: https://doi.org/10.1016/j.media.2021.102126.
- J. H. Legarreta, L. Petit, P.-M. Jodoin, and M. Descoteaux, "Clustering in Tractography Using Autoencoders (CINTA)," in Computational Diffusion MRI (CDMRI) Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshop, 2022, vol. 13722, pp. 125–136. doi: https://doi.org/10.1007/978-3-031-21206-2_11.