AutoPET Challenge 2022: Automatic Segmentation of Whole-body Tumor Lesion Based on Deep Learning and FDG PET/CT

Ronneberger O, Fischer P, and Brox T. U-net: Convolutional networks for biomedical image segmentation[C]//International Conference on Medical image computing and computer-assisted intervention. Springer, Cham, 2015: 234-241

2015

Earlier work this paper cites.

Hu J, Shen L, and Sun G. Squeeze-and-excitation networks[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 7132-7141

2018

Cited alongside, same era.

Radosavovic I., Kosaraju R. P., Girshick R., He K., and Dollár P. Designing network design spaces[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020: 10428-10436

2020

Later among the works it cites.