Table 9.

Quantitative comparison of segmentation and classification methods using GAN models. Accuracy, area under curve (AUC), and dice similarity coefficient (DSC) are reported for comparison. SGD is the abbreviation for stochastic gradient descent, ReLu for rectified linear unit, lr for learning rate, and AF for activation function

Method	Optimizer	AF	LR Scheduling	Images size	Dataset	Pre-processing step	Technique	Accuracy	AUC	DSC
DL [106]	Adam	ReLu, Leaky ReLU	lr = 0.001	1204 $\times$ 1024	CXR-14	Data augmentation	CycleGAN, VGG-16, ResNet, JRS	–	–	88.9
DL [21]	Adam	–	lr = 0.002 which is reduced after every 100 epochs	512 $\times$ 512	MC, JSRT	Image resizing and rescaling	Semantic aware GAN, ResNet-101, dilated convolutions	–	–	94.5
DL [34]	–	ReLu	lr = 0.01	400 $\times$ 400	MC, JSRT	Image resizing	Residual FCN, Critic FCN	–	–	97.3
DL [117]	Adam, Nesterov	–	lr = 0.0004 with ${\beta }_1$= 0.5, ${\beta }_2$= 0.999, 0.00001 with a momentum of 0.99	128 $\times$ 128	JSRT	Image resizing	DCGAN, UNet architecture	–	–	94.6
DL [115]	Adam	ReLu, Leaky ReLu	lr = 0.0002 and decay rate of 0.5	256 $\times$ 256, 512 $\times$ 512	MC, Shenzhen, JSRT	Image resizing	Skip connections, conditional GAN, pixel GAN, patch GAN	–	–	97.4
DL [42]	SGD	ReLu	–	512 $\times$ 512	MC, Shenzhen, JSRT	Image resizing, histogram equalization	Attention UNet, Critic FCN, Focal Tversky Loss	–	–	97.5
DL [68]	Adam	ReLu	lr = 0.00001	128 $\times$ 128	MC, Shenzhen, JSRT	Image resizing and normalization	Adversarial Pyramid Progressive Attention UNet, KL divergence with Tversky loss	75.8	–	97.6
DL [105]	–	Leaky ReLu	–	128 $\times$ 128	PLCO, Indiana	Image resizing	GAN, CNN	93.7	–	–
DL [163]	Adam	Softmax	lr = 0.0002 for first 100 epochs	512 $\times$ 512	RSNA${}^{\mathrm{a}}$, CXR dataset [83]	Image resizing	ResNet-18, ResNet-50, CycleGAN, semantic modeling	93.1	96.3	–
DL [165]	Adam	Leaky ReLu	lr = 0.0005	64 $\times$ 64	CXR-14	Image resizing and no augmentation is performed	GAN, U-Net autoencoder, CNN discriminator, One class learning	–	84.1	–
DL [174]	Adam	ReLu, Leaky Relu	lr = 0.0002 with $\beta$= 0.5	112 $\times$ 112	COVID-19	Image resizing and normalization	VGG-16, Auxiliary Classifier Generative Adversarial Network, PCA	95.0	–	–

${}^{\mathrm{a}}$https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data