Table IV. KL divergence and Wasserstein distance between synthetic data distribution and real data distribution.

Distribution similarity	Kullback–Leibler (KL) divergence					Wasserstein Distance (WD)
	LVEDV	LVESV	RVEDV	RVESV	LVM	LVEDV	LVESV	RVEDV	RVESV	LVM
CGAN [34]	0.023 ±0.001	0.019 ±0.001	0.036±0.004	0.022 ±0.001	0.050±0.006	33.687±1.173	19.982±0.025	41.643±4.161	17.434±0.036	35.395±2.933
CVAE [48]	0.039±0.005	0.041±0.004	0.042±0.004	0.034±0.003	0.030±0.003	11.929 ±2.116	7.017±0.964	14.680±2.869	9.665±1.051	10.365±1.703
CVAE-GAN [6]	0.153±0.025	0.023±0.003	0.046±0.006	0.064±0.008	0.098±0.019	27.001±2.809	8.425±1.771	24.614±3.202	9.748±2.675	43.251±4.566
Proposed	0.034±0.002	0.043±0.002	0.034 ±0.002	0.039±0.002	0.031 ±0.002	15.053±3.597	5.773 ±1.358	12.214 ±2.408	9.182 ±2.145	9.215 ±1.713