Table 10.

Studies for nasopharyngeal carcinoma (NPC) segmentation based on deep learning (DL).

Author, Year, Reference	Image	Sample Size	Modeling	Model Evaluation
Men, K. (2017) [129]	CT	230	DDNN and VGG-16	DSC GTVnx 80.9% GTVnd 62.3% CTV 82.6%
Li, Q. (2018) [130]	MRI	29	CNN	DSC 0.89
Wang, Y. (2018) [131]	MRI	15	DCNN	DSC 0.79
Ma, Z. (2018) [132]	CT, MRI	50	Multi-modality CNN	DSC 0.636 (CT), 0.712 (MRI)
Daoud, B. (2019) [133]	CT	70	CNN	DSC 0.91
Lin, L. (2019) [134]	MRI	1021	3D-CNN	DSC 0.79
Liang, S. (2019) [135]	CT	185	CNN	DSC 0.689–0.937
Zhong, T. (2019) [136]	CT	140	CNN	DSC Parotids 0.92 Thyroids 0.92 Optic nerves 0.89
Ma, Z. (2019) [137]	CT, MRI	90	Single-modality CNN multi-modality CNN	DSC 0.746 (CT), 0.752 (MRI)
Li, S. (2019) [138]	CT	502	U-Net (CNN)	DSC Lymph nodes 0.659 Tumor 0.74
Xue, X. (2020) [139]	CT	150	SI-Net and U-Net	DSC 0.84
Chen, H. (2020) [140]	MRI	149	3D-CNN	DSC 0.724
Guo, F. (2020) [141]	MRI	120	3D-CNN	DSC 0.737
Ye, Y. (2020) [142]	MRI	44	Dense connectivity embedding U-net	DSC 0.87
Li, Y. (2020) [143]	MRI	596	ResNet-101	DSC 0.703
Jin, Z. (2020) [144]	CT	90	ResSE-UNet	DSC 0.84
Wang, X. (2020) [145]	CT	205	3D U-Net	DSC 0.827
Ke, L. (2020) [128]	MRI	4100	3D DenseNet	DSC 0.77
Wong, L.M. (2021) [146]	MRI	195	CNN	DSC 0.73
Bai, X. (2021) [147]	MRI	60	ResNeXt-50 and U-Net	DSC 0.618