Fetching the paper…
Reading the bibliography…
Early detection of pulmonary cancer is the most promising way to enhance a patient's chance for survival.
The national lung screening trial research team. reduced lung-cancer mortality with low-dose computed tomographic screening
D. S. Alberts · 2011
Earlier work this paper cites.
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, and et al · 2011
Earlier work this paper cites.
M. Lin, Q. Chen, and S. Yan · 2013
Earlier work this paper cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R.B. Girshick, and J. Sun · 2015
Cited alongside, same era.
Cancer statistics, 2015
R. L. Siegel, K. D. Miller, and A. Jemal · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Cited alongside, same era.
Large scale validation of the m5l lung cad on heterogeneous ct datasets
E. L. Torres, E. Fiorina, F. Pennazio, and et al · 2015
Cited alongside, same era.
Pulmonary nodule detection in ct images: false positive reduction using multi-view convolutional networks
A. A. A. Setio, F. Ciompi, G. Litjens, and et al · 2016
Later among the works it cites.
A. A. A. Setio, A. Traverso, T. Bel, and et al · 2016
Later among the works it cites.
S. Zagoruyko and N. Komodakis · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…