# Cycle Consistent Generative Motion Artifact Correction in Coronary Computed Tomography Angiography
## 4 Results
### Clinical Data
#### 4.2.4 Qualitative Evaluation  
One experienced reader evaluated the degree of motion artifacts in coronary artery images using a 5-point Likert scale. The assessment was blinded; the reader was unaware of whether the images were pre- or post-application of the proposed motion correction methods. Images were randomly presented without any identification, including both original and motion-corrected patches. Table 4 shows the distribution of the Likert scale scores for the test patches before and after motion correction using different methods, namely, Original, [PERSON] et al., pix2 pix, and CycleGAN. Initially, a significant majority of images (98.5%) were rated in the lower categories of the Likert scale (1, 2, and 3), indicating a high degree of motion artifacts. However, after applying the motion correction methods, this percentage substantially decreased to 35% for Original and further reduced with the application of advanced methods like pix2 pix and CycleGAN, as demonstrated by the lower frequency of categories 1, 2, and 3 (0.5%, 3.5%, and 32.1% for pix2 pix; 0.5%, 3.1%, and 30.6% for CycleGAN, respectively). \begin{table}
\begin{tabular}{l l c c c} \hline \hline
**Motion Artifact Metric** & **Method** & **Median** & **IQR** & _p_**-Value** \\ \hline \multirow{3}{*}{Isotropy} & Original & 0.40 & 0.30–0.58 & \\  & [PERSON] et al. [14] & 0.63 & 0.46–0.75 & \textless{}0.001 \\  & pix2 pix & 0.75 & 0.65–0.83 & \textless{}0.001 \\  & Proposed (CycleGAN) & 0.74 & 0.63–0.84 & \textless{}0.001 \\ \hline \multirow{3}{*}{Fold Overlap Ratio (FOR)} & Original & 0.59 & 0.54–0.62 & \\  & [PERSON] et al. [14] & 0.63 & 0.59–0.67 & \textless{}0.001 \\  & pix2 pix & 0.79 & 0.78–0.81 & \textless{}0.001 \\  & hlProposed (CycleGAN) & 0.8 & 0.79–0.81 & \textless{}0.001 \\ \hline \multirow{3}{*}{Low-Intensity Region Score (LIRS)} & Original & 0.92 & 0.89–0.95 & \\  & [PERSON] et al. [14] & 0.97 & 0.93–1.0 & \textless{}0.001 \\  & pix2 pix & 1.0 & 1.0–1.0 & \textless{}0.001 \\  & Proposed (CycleGAN) & 1.0 & 1.0–1.0 & \textless{}0.001 \\ \hline \multirow{3}{*}{Motion Artifact Score (MAS)} & Original & 0.54 & 0.48– 0.59 & \\  & [PERSON] et al. [14] & 0.61 & 0.55–0.67 & \textless{}0.001 \\ \cline{1-1}  & pix2 pix & 0.79 & 0.78–0.81 & \textless{}0.001 \\ \cline{1-1}  & Proposed (CycleGAN) & 0.8 & 0.79–0.81 & \textless{}0.001 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of Methods Across Different Metrics. Moreover, the mean score based on the Likert scale improved markedly from 1.43 (\(\pm\)0.66) in the original images to 3.80 (\(\pm\)0.87) for [PERSON] et al. (2014), 3.82 (\(\pm\)0.84) for pix2 pix, and 3.88 (\(\pm\)0.85) for CycleGAN, indicating a significant reduction in motion artifacts. The statistical significance of these improvements is confirmed with _p_-values smaller than 0.001. In our comparative analysis of pix2 pix and CycleGAN, we observed a notable superiority in the performance of CycleGAN, particularly in the context of motion artifact correction in coronary artery imaging. While both methods showed significant improvements in reducing motion artifacts, CycleGAN demonstrated a slight edge over pix2 pix in several key metrics. For instance, CycleGAN's ability to better preserve the structural integrity of the coronary arteries was evident, as indicated by its higher scores in the Likert scale evaluation. Specifically, CycleGAN achieved a mean score of 3.88 (\(\pm\)0.85) compared to pix2 pix's 3.82 (\(\pm\)0.84), suggesting a more effective reduction in noticeable motion artifacts. The sample results showcasing the comparative effectiveness of pix2 pix and CycleGAN in motion artifact correction are illustrated in Figures 8 and 9. Accompanying each image set are the Likert score changes and source information, providing a comprehensive overview of the improvements. Figure 8 highlights the varying degrees of enhancements achieved.