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Semantic image segmentation plays an important role in modeling patient-specific anatomy.
Sørensen, T.: A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on danish commons. Biol. Skr. (1948)
1948
Earlier work this paper cites.
Porter, C.R., Crawford, E.D.: Combining artificial neural networks and transrectal ultrasound in the diagnosis of prostate cancer. Oncology (Williston Park, NY) (2003)
2003
Earlier work this paper cites.
Krähenbühl, P., Koltun, V.: Efficient inference in fully connected crfs with gaussian edge potentials. In: NIPS (2011)
2011
Earlier work this paper cites.
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS (2012)
2012
Earlier work this paper cites.
Ji, S., Xu, W., Yang, M., Yu, K.: 3d convolutional neural networks for human action recognition. IEEE transactions on pattern analysis and machine intelligence (2013)
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
Chollet, F., et al.: Keras. https://github.com/fchollet/keras
2015
Cited alongside, same era.
2015
Cited alongside, same era.
Zettinig, O., Shah, A., Hennersperger, C., Eiber, M., Kroll, C., Kübler, H., Maurer, T., Milletarì, F., Rackerseder, J., zu Berge, C.S., et al.: Multimodal image-guided prostate fusion biopsy based on automatic deformable registration. IJCARS (2015)
2015
Cited alongside, same era.
Bertasius, G., Shi, J., Torresani, L.: Semantic segmentation with boundary neural fields. In: CVPR (2016)
2016
Cited alongside, same era.
Merkow, J., Marsden, A., Kriegman, D., Tu, Z.: Dense volume-to-volume vascular boundary detection. In: IJCARS (2016)
2016
Later among the works it cites.
Milletari, F., Navab, N., Ahmadi, S.A.: V-net: Fully convolutional neural networks for volumetric medical image segmentation. In: 3D Vision (3DV) (2016)
2016
Later among the works it cites.
Shin, H.C., Roth, H.R., Gao, M., Lu, L., Xu, Z., Nogues, I., Yao, J., Mollura, D., Summers, R.M.: Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning. IEEE TMI (2016)
2016
Later among the works it cites.
2017
Later among the works it cites.
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2016
Cited alongside, same era.
Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., Brox, T., Ronneberger, O.: 3d u-net: learning dense volumetric segmentation from sparse annotation. In: MICCAI (2016)
2016
Cited alongside, same era.
2018
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