Uncertainty Estimation in Deep 2D Echocardiography Segmentation

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2013

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Kendall, A., Badrinarayanan, V., Cipolla, R.: Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding. arXiv preprint arXiv:1511.02680 (2015)

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He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 770–778 (2016)

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Lakshminarayanan, B., Pritzel, A., Blundell, C.: Simple and scalable predictive uncertainty estimation using deep ensembles. In: Advances in neural information processing systems. pp. 6402–6413 (2017)

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Leibig, C., Allken, V., Ayhan, M.S., Berens, P., Wahl, S.: Leveraging uncertainty information from deep neural networks for disease detection. Scientific reports 7

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Ayhan, M.S., Berens, P.: Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks (2018)

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Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. In: Computer Vision – ECCV 2018, pp. 833–851. Springer International Publishing (2018). https://doi.org/10.1007/978-3-030-01234-2_49, https://doi.org/10.1007%2F978-3-030-01234-2˙49

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Kohl, S., Romera-Paredes, B., Meyer, C., De Fauw, J., Ledsam, J.R., Maier-Hein, K., Eslami, S.A., Rezende, D.J., Ronneberger, O.: A probabilistic u-net for segmentation of ambiguous images. In: Advances in Neural Information Processing Systems. pp. 6965–6975 (2018)

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Hoebel, K., Chang, K., Patel, J., Singh, P., Kalpathy-Cramer, J.: Give me (un) certainty–An exploration of parameters that affect segmentation uncertainty. arXiv preprint arXiv:1911.06357 (2019)

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Leclerc, S., Smistad, E., Pedrosa, J., Østvik, A., Cervenansky, F., Espinosa, F., Espeland, T., Berg, E.A.R., Jodoin, P.M., Grenier, T., et al.: Deep learning for segmentation using an open large-scale dataset in 2D echocardiography. IEEE transactions on medical imaging 38

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Ouyang, D., He, B., Ghorbani, A., Langlotz, C., Heidenreich, P.A., Harrington, R.A., Liang, D.H., Ashley, E.A., Zou, J.Y.: Interpretable AI for beat-to-beat cardiac function assessment. medRxiv p. 19012419 (2019)

2019

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Wang, G., Li, W., Aertsen, M., Deprest, J., Ourselin, S., Vercauteren, T.: Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks. Neurocomputing 335