Fetching the paper…
Reading the bibliography…
Data availability plays a critical role for the performance of deep learning systems.
Karwoski, R.A., Bartholmai, B., Zavaletta, V.A., et al.: Processing of ct images for analysis of diffuse lung disease in the lung tissue research consortium. In: Proc. SPIE 6916 (2008)
2008
Earlier work this paper cites.
Armato, S.G., McLennan, G., Bidaut, L., et al.: The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans. Medical physics 38(2), 915–931 (2011)
2011
Earlier work this paper cites.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., et al.: Generative adversarial nets. In: Advances in neural information processing systems. pp. 2672–2680 (2014)
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
2015
Cited alongside, same era.
Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., et al.: 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation, pp. 424–432. Springer (2016)
2016
Cited alongside, same era.
Pathak, D., Krahenbuhl, P., Donahue, J., et al.: Context encoders: Feature learning by inpainting. In: Proc. IEEE CVPR. pp. 2536–2544 (2016)
2016
Cited alongside, same era.
Chuquicusma, M.J., Hussein, S., Burt, J., Bagci, U.: How to fool radiologists with generative adversarial networks? a visual turing test for lung cancer diagnosis. In: Proc. IEEE ISBI. pp. 240–244 (2017)
2017
Cited alongside, same era.
Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proc. IEEE CVPR. pp. 1125–1134 (2017)
2017
Later among the works it cites.
Jin, D., Xu, Z., Harrison, A.P., et al.: 3d convolutional neural networks with graph refinement for airway segmentation using incomplete data labels. In: International Workshop on Machine Learning in Medical Imaging. pp. 141–149. Springer (2017)
2017
Later among the works it cites.
Nie, D., Trullo, R., Lian, J., et al.: Medical image synthesis with context-aware generative adversarial networks. In: Proc. MICCAI. pp. 417–425. Springer (2017)
2017
Later among the works it cites.
Wang, X., Peng, Y., Lu, L., et al.: Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases. In: Proc. IEEE CVPR. pp. 3462–3471 (2017)
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Harrison, A.P., Xu, Z., George, K., et al.: Progressive and multi-path holistically nested neural networks for pathological lung segmentation from ct images. In: Proc. MICCAI. pp. 621–629. Springer (2017)
2017
Cited alongside, same era.
Wolterink, J.M., Dinkla, A.M., Savenije, M.H., et al.: Deep mr to ct synthesis using unpaired data. In: International Workshop on Simulation and Synthesis in Medical Imaging. pp. 14–23. Springer (2017)
2017
Later among the works it cites.