Table 6.

GAN selected studies.

Authors Name and Year	Methods	Results	Authors Suggestions/Conclusions
Kim et al., (2020) [99]	CNN, GLCIC, Edge Connect	Improvement of 0.004 mm in the tooth segmentation	The segmentation approach for complete arch intraoral scan data is efficient, time-saving, and as accurate as a manual segmentation method.
Kokomoto et al., (2021) [100]	PGGAN	p value < 0.0001	The quantity of trained photos has a significant impact on PGGAN’s ability to generate realistic visuals.