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The recent breakthroughs of Neural Architecture Search (NAS) have motivated various applications in medical image segmentation.
2007
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Heimann, T., Van Ginneken, B., Styner, M.A., Arzhaeva, Y., Aurich, V., Bauer, C., Beck, A., Becker, C., Beichel, R., Bekes, G., et al.: Comparison and evaluation of methods for liver segmentation from ct datasets. IEEE transactions on medical 28
2009
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Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., Vincent, G., Guillard, G., Birbeck, N., Zhang, J., et al.: Evaluation of prostate segmentation algorithms for mri: the promise12 challenge. Medical image analysis 18
2014
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2015
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2015
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2016
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2018
Cited alongside, same era.
2018
Cited alongside, same era.
Zoph, B., Vasudevan, V., Shlens, J., Le Q. V.: Learning transferable architectures for scalable image recognition. In CVPR (2018)
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Zoph, B., Vasudevan, V., Shlens, J., Le, Q.V.: Learning transferable architectures for scalable image recognition. In CVPR (2018)
Dong, N., Xu, M., Liang, X., Jiang, Y., Dai, W., Xing, E.: Neural Architecture Search for Adversarial Medical Image Segmentation. In MICCAI (2019)
2019
Later among the works it cites.
Kim, S., Kim, I., Lim, S., Baek, W., Kim, C., Cho, H., Yoon, B., Kim, T.: Scalable Neural Architecture Search for 3D Medical Image Segmentation. In MICCAI (2019)
2019
Later among the works it cites.
Weng, Y., Zhou, T., Li, Y., Qiu, X.: NAS-Unet: Neural architecture search for medical image segmentation. IEEE Access 7
2019
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2019
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2018
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2019
Cited alongside, same era.
2019
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2019
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