UNet++: A Nested U-Net Architecture for Medical Image Segmentation

The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans

S. G. Armato, G. McLennan, L. Bidaut, M. F. McNitt-Gray, C. R. Meyer, A. P. Reeves, B. Zhao, D. R. Aberle, C. I. Henschke, E. A. Hoffman, et al · 2011

Earlier work this paper cites.

Deeply-supervised nets

C.-Y. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu · 2015

Earlier work this paper cites.

Fully convolutional networks for semantic segmentation

J. Long, E. Shelhamer, and T. Darrell · 2015

Earlier work this paper cites.

U-net: Convolutional networks for biomedical image segmentation

O. Ronneberger, P. Fischer, and T. Brox · 2015

Earlier work this paper cites.

The importance of skip connections in biomedical image segmentation

M. Drozdzal, E. Vorontsov, G. Chartrand, S. Kadoury, and C. Pal · 2016

Cited alongside, same era.

Convolutional neural networks for medical image analysis: Full training or fine tuning?

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and J. Liang · 2016

Cited alongside, same era.

Residual conv-deconv grid network for semantic segmentation

Original

D. Fourure, R. Emonet, E. Fromont, D. Muselet, A. Tremeau, and C. Wolf · 2017

Cited alongside, same era.

Mask r-cnn

K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017

Cited alongside, same era.

Densely connected convolutional networks

G. Huang, Z. Liu, K. Q. Weinberger, and L. van der Maaten · 2017

Later among the works it cites.

H-denseunet: Hybrid densely connected unet for liver and liver tumor segmentation from ct volumes

Original

X. Li, H. Chen, X. Qi, Q. Dou, C.-W. Fu, and P. A. Heng · 2017

Later among the works it cites.

Fine-tuning convolutional neural networks for biomedical image analysis: actively and incrementally

Original

Z. Zhou, J. Shin, L. Zhang, S. Gurudu, M. Gotway, and J. Liang · 2017

Later among the works it cites.