Table 3. Summary of recently published false-positive reduction algorithms together with their reported sensitivity and false-positive rates.

Year	Authors	Identified features	True positive rate	False-positive rate
2009	Guo et al. (34)	Shape features	94.77%	N/A
2009	Murphy et al. (35)	Shape, curvedness	80.00%	4.20
2009	Retico et al. (36)	Morphological features, texture features	72.00%	6.00
2010	Sousa et al. (37)	Shape, texture, gradient, histogram, spatial features	84.84%	0.42
2010	Messay et al. (38)	Shape, intensity, gradient	82.66%	3.00
2013	Orozco et al. (39)	Texture features	84.00%	7.00
2013	Tartar et al. (40)	Shape features	89.60%	7.90
2014	Teramoto et al. (41)	Shape features, intensity	83.00%	5.00
2018	Gong et al. (42)	Intensity, shape, texture features	79.30%	4.00
2020	Sun et al. (43)	S-transform	97.87%	6.70