# A Systematic Literature Review on Applications of GAN-Synthesized Images for Brain MRI
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Evaluation Metric** & **FR/NR** & **Description** & **Assessment Method** & **Ref. No.** \\ \hline Average symmetric & FR & ASSD measures the average of all Euclidean & Segmented image & [53, 77, 168] \\ surface distance (ASSD) & FR & distances between two image volumes. & \\ Blind / Reference-less & & BRISQUE focuses natural scene statistics (NSS) & \\ Image Spatial Quality & NR & such as ringing, blur, and blocking. It quantifies the reduction of naturalness by locally & Whole image & [33, 58, 86] \\ Evaluator (BRISQUE) & & normalizing the luminance coefficients. & \\ Dice Similarity Coefficient & & DSC measures the spatial overlap and provides a reproducibulity validation score for image segmentation. & Segmented image & [70, 77, 99, 83, 96, 144] \\ (DSC) & FR & The distance between Gaussian distributions of synthetic and real images is FID or the Wasserstein-2 distance. & Whole image & [35, 98, 99, 120] \\ (FID) & FR & HD measures the maximum Euclidean distance & \\ Hausdorff Distance (HD)95 & FR & between all surface points of two image volumes. & Segmented image & [115] \\ Jaccard similarity coefficient (JSC) & FR & It is a value used to compare the similarity and diversity of images recognized as Intersection over Union. & Segmented image & [98, 99, 159] \\ Maximum Mean & FR & MMD measures the dissimilarity between the probability distribution of real images over the space of natural images and parameterized distribution of the generated images. & Whole image & [32] \\  & & MID measures the association between corresponding synthetic images in different modalities. It first evaluates the mutual information of synthetic image pairs and real image pairs and then computes their absolute difference. & Whole image & [84, 99] \\ Normalized Mean & FR & NMAE measures the estimation errors of a specific color component between the original and synthetic images. & Whole image & [33, 74, 88] \\ (NMAE) & NR & NMI expresses the amount of information synthetic images carry regarding the original image. & Whole image & [140, 148] \\ Normalized & FR & NCC evaluates the degree to which the synthetic and original image signals are similar. It is an elementary approach to match two image patch positions. & Segmented image & [25] \\ (NMAE) & FR & NIQE is a distance-based measure of natural images divergence from statistical consistency. & Whole image & [33, 41, 58, 88] \\ Naturalness Image & NR & The metric quantifies image quality according to the level of distortions. & Whole image & [33, 41, 58, 88] \\ Quality Evaluator (NIQE) & FR & It is an expression for the ratio between the maximum possible power of the original image & Whole image & [48, 56, 59, 73, 74, 75, 85, 88] \\ Peak Signal-to-Noise Ratio (PSNR) & FR & The number of images is a particular image & Whole image & [48, 56, 59, 73, 74, 75, 85, 88] \\ (PSNR) & FR & The number of images is a particular image & Whole image & [38, 59, 73, 74, 75, 88] \\ Structural Similarity Index & FR & The number of images is a particular image & Whole image & [38, 59, 73, 74, 75, 88] \\ Measures (SSIM) & FR & The number of images is a particular image & Whole image & [68, 72, 75, 99, 140] \\ Root-Mean-Square Error (RMSE) & FR & The number of images is a particular image & Whole image & [14, 141, 142] \\ Universal Quality Index (UQI) & FR & Image distortion is the product of loss of correlation, luminance, and contrast distortion. & Whole image & [14] \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Comparative study of evaluation metrics used in this SLR. Unsupervised learning to produce an image from the features of the real image. This SLR shows that GAN-synthesized images have potential use in data augmentation, yet they have also been immensely used for other image applications. In addition, GAN can speed up the whole analysis step in radiology [11]. This SLR includes papers published in Q1 or Q2 journals and conferences in the Web of Science and Scopus databases.