Table 5.

Benchmarking table.

A1	A2	A3	A4	A5	A6	A7	A8	A9	A10	A11	A12	A13	A14	A15	A16	A17	A18
Author	Year	Model	Classifier	# Patients	# Img	# GT Tracings	Focus	Objective	Modality	Opt&	Augm#	DSC	ACC	AUC	Rad *	CE	Bench
Ding et al. [109]	2021	MT-nCov-Net	Res2Net50	189	36485	8	Segm.	Lesion	CT	✓	✓	0.86	99.61	0.92	3	✓	✓
Hou et al. [110]	2021	Improved Canny edge detector	NA	271	812	NA	NA	Lesion	CT	✓	🗶	🗶	🗶	🗶	🗶	🗶	🗶
Lizzi et al. [112]	2021	Cascaded UNet	NA	NA	NA	NA	Class. + Segm.	Lesion	CT	✓	✓	0.62	93	🗶	1	✓	🗶
Qi et al. [113]	2021	DR-MIL	(ResNet-50 and Xception	241	2410	1	NA	NA	CT	🗶	✓	🗶	95	0.943	🗶	✓	✓
Paluru et al. [114]	2021	Anam-Net	custom (UNet + ENet)	69	4339	1	Segm.	Lesion	CT	✓	🗶	0.77	98	🗶	🗶	✓	✓
Zhang et al. [115]	2020	CoSinGAN	NA	70	704	1	Class. + Segm.	Lesion	CT	✓	✓	0.75	🗶	🗶	🗶	🗶	✓
Singh et al. [111]	2021	LungINFseg	Modified UNet	20	1800	1	Heatmap + Segm.	Lesion	CT	✓	✓	0.8	80	🗶	🗶	🗶	✓
Amyar et al. [117]	2020	UNet	NA	1369	1369	1	Class. + Segm.	Lesion	CT	✓	🗶	0.88	94	0.97	🗶	✓	✓
Budak et al. [116]	2021	A-SegNet	NA	69	473	1	Segm.	Lesion	CT	✓	🗶	0.89	🗶	🗶	🗶	🗶	🗶
Cai et al. [118]	2020	UNet	NA	99	250	1	Class. + Segm.	Lung + lesion + predict ICU stay	CT	✓	🗶	0.77	🗶	🗶	🗶	✓	🗶
Ma et al. [119]	2021	UNet	NA	70	NA	1	Segm.	Lesion	CT	✓	🗶	0.67	🗶	🗶	2	✓	✓
Kuchana et al. [120]	2020	UNet and attention UNet,	NA	50	929	1	Segm.	Lung + lesion	CT	✓	🗶	0.84	🗶	🗶	1	🗶	🗶
Suri et al. [proposed]	2021	PSPNet, VGG-SegNet ResNet-SegNet VGG-UNet ResNet-UNet	VGG, ResNet	40	3000	2	Segm.	Lesion	CT	✓	🗶	0.79 0.79 0.77 0.80 0.83	0.95 0.96 0.95 0.97 0.98	0.95 0.94 0.87 0.91 0.87	2	✓	✓

* Rad: radiologist; Augm#: augmentation; Opt&: optimization; CE: clinical evaluation; Bench: benchmarking; # Img: number of images.