Fetal Brain MRI Measurements Using a Deep Learning Landmark Network with Reliability Estimation

Author:

Avisdris NetanellORCID,Ben Bashat Dafna,Ben-Sira Liat,Joskowicz Leo

Publisher

Springer International Publishing

Reference22 articles.

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2. Arthur, D., Vassilvitskii, S.: K-means++: the advantages of careful seeding. In: Proceedings of ACM-SIAM Symposium on Discrete Algorithms (2007)

3. Avisdris, N., et al.: Automatic linear measurements of the fetal brain with deep neural networks. Int. J. Comput. Assist. Radiol. Surg. (2021). https://doi.org/10.1007/s11548-021-02436-8

4. Ayhan, M.S., Berens, P.: Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks. In: International Conference on Medical Imaging with Deep Learning (2018)

5. Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 39(1), 1–22 (1977)

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