Could artificial intelligence-powered colonoscopies change the future of colorectal cancer screening?

Table 2 Performance comparison of studied models[110]

Model (year)	CVC-ClinicDB				Kvasir-SEG				CVC-ColonDB				EndoScene
	Dice	IoU	Rec	Prec	Dice	IoU	Rec	Prec	Dice	IoU	Rec	Prec	Dice	IoU	Rec	Prec
UNet (2015)	29.83	19.57	75.07	22.76	39.76	27.53	84.78	31.28	15.38	9.87	85.321	14.53	29.21	19.54	58.73	25.88
U2Net (2020)	91.06	84.61	91.58	92.322	86.52	77.45	85.89	89.8	82.28	73.43	79.53	88.432	90.96	85.532	91.23	92.172
I2UNet (2024)	92.322	87.602	94.141	78.01	87.75	84.451	86.70	88.59	75.05	65.94	69.89	49.50	87.41	77.87	92.382	77.53
SR-AttNet (2023)	85.20	76.79	88.92	84.14	88.02	80.83	88.372	90.892	83.352	76.422	84.09	83.41	91.032	85.04	90.99	92.02
FoccusU2Net (proposed)	93.61	89.31	93.12	93.31	89.81	84.32	88.982	91.142	86.41	77.61	84.22	93.21	93.61	88.11	93.71	94.81

¹The best values.

²The second-best values.

Dice score: A metric used to measure the resemblance of two groups; IoU: A metric used to evaluate the accuracy of annotation, segmentation and object detection algorithms; Rec: Recall the true positive rate; Prec: Precision the degree of accuracy.