Synthetic Balancing of Cardiac MRI Datasets
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-66958-3_26
Reference21 articles.
1. Chen, C., et al.: Deep learning for cardiac image segmentation: a review (2019). arXiv:1911.03723 [eess.IV]
2. Campello, V.M., et al.: Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M &Ms challenge. IEEE Trans. Med. Imaging 40(12), 3543–3554 (2021). https://doi.org/10.1109/TMI.2021.3090082
3. Bai, W., et al.: A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Med. Image Analysis 26(1), 133–145 (2015). https://doi.org/10.1016/j.media.2015.08.009
4. Park, T., Efros, A.A., Zhang, R., Zhu, J.-Y.: Contrastive learning for unpaired image-to-image translation. In: European Conference on Computer Vision (2020)
5. Banerjee, A., et al.: A completely automated pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance slices. Philos. Trans. A Math. Phys. Eng. Sci. 379(2212), 20200257 (2021)
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