# Classification of Valvular Regurgitation Using Echocardiography
## 4 Experimental Results
### Classification Comparison with Existing Methodologies
\begin{table}
\begin{tabular}{l l c c c c c c c c c} \hline \hline
**Method** & \begin{tabular}{c} **Performance** \\ **Metrics** \\ \end{tabular} & \begin{tabular}{c} **With Segmentation** \\ **10\%** \\ \end{tabular} & \begin{tabular}{c} **Segmentation** \\ **20\%** \\ \end{tabular} & \begin{tabular}{c} **Without Segmentation** \\ **40\%** \\ \end{tabular} & \begin{tabular}{c} **Without Segmentation** \\ **50\%** \\ \end{tabular} & \begin{tabular}{c} **50\%** \\ \end{tabular} & \begin{tabular}{c} **10\%** \\ \end{tabular} & \begin{tabular}{c} **20\%** \\ \end{tabular} & \begin{tabular}{c} **30\%** \\ \end{tabular} & \
\begin{tabular}{c} **40\%** \\ \end{tabular} &
\begin{tabular}{c} **50\%** \\ \end{tabular} \\ \hline SVM (Ref) & Accuracy & 0.88 & 0.66 & 0.50 & 0.51 & 0.50 & 1 & 0.57 & 0.47 & 0.42 & 0.34 \\  & Precision & 0.90 & 0.66 & 0.56 & 0.52 & 0.56 & 1 & 0.55 & 0.46 & 0.44 & 0.34 \\  & Recall & 0.90 & 0.73 & 0.50 & 0.48 & 0.17 & 1 & 0.60 & 0.53 & 0.53 & 0.51 \\  & F1-score & 0.88 & 0.63 & 0.50 & 0.48 & 0.43 & 1 & 0.56 & 0.43 & 0.43 & 0.73 \\ \hline PCA-SVM (Ref) & Accuracy & 0.70 & 0.71 & 0.71 & 0.64 & 0.57 & 0.85 & 0.57 & 0.52 & 0.50 & 0.51 \\  & Precision & 0.66 & 0.69 & 0.75 & 0.66 & 0.58 & 0.89 & 0.72 & 0.51 & 0.52 & 0.51 \\  & Recall & 0.50 & 0.83 & 0.81 & 0.74 & 0.58 & 0.89 & 0.49 & 0.57 & 0.64 & 0.70 \\  & F1-score & 0.89 & 0.63 & 0.50 & 0.48 & 0.43 & 0.86 & 0.64 & 0.52 & 0.50 & 0.46 \\ \hline SVM (Red) & Accuracy & 0.33 & 0.40 & 0.42 & 0.40 & 0.33 & 0.90 & 0.88 & 0.90 & 0.90 & 0.94 \\  & Precision & 0.33 & 0.33 & 0.66 & 0.58 & 0.46 & 0.77 & 0.79 & 0.83 & 0.83 & 0.92 \\  & Recall & 0.16 & 0.16 & 0.27 & 0.26 & 0.25 & 0.91 & 0.90 & 0.92 & 0.92 & 0.94 \\  & F1-score & 0.22 & 0.22 & 0.38 & 0.37 & 0.32 & 0.84 & 0.84 & 0.87 & 0.87 & 0.93 \\ \hline PCA-SVM (Red) & Accuracy & 0.54 & 0.58 & 0.47 & 0.51 & 0.47 & 1 & 0.93 & 0.95 & 0.93 & 0.69 \\  & Precision & 0.51 & 0.56 & 0.47 & 0.40 & 0.48 & 1 & 0.93 & 0.94 & 0.91 & 0.73 \\  & Recall & 0.54 & 0.57 & 0.47 & 0.40 & 0.48 & 1 & 0.93 & 0.96 & 0.94 & 0.80 \\  & F1-score & 0.53 & 0.56 & 0.46 & 0.50 & 0.48 & 1 & 0.93 & 0.95 & 0.92 & 0.77 \\ \hline \multirow{4}{*}{Proposed (Ref)} & Accuracy & 1 & 0.69 & 0.92 & 0.84 & 1 & 0.90 & 1 & 1 & 1 & 0.92 \\  & Precision & 1 & 0.55 & 0.91 & 0.86 & 1 & 0.88 & 1 & 1 & 1 & 0.95 \\  & Recall & 1 & 0.51 & 0.96 & 0.88 & 1 & 0.86 & 1 & 1 & 1 & 0.93 \\  & F1-score & 1 & 0.50 & 0.93 & 0.84 & 1 & 0.84 & 1 & 1 & 1 & 0.93 \\ \hline \multirow{4}{*}{Proposed (Red)} & Accuracy & 0.71 & 0.73 & 0.85 & 0.50 & 0.71 & 1 & 0.90 & 1 & 0.90 & 1 \\  & Precision & 0.70 & 0.71 & 0.84 & 0.53 & 0.72 & 1 & 0.89 & 1 & 0.89 & 1 \\ \cline{1-1}  & Recall & 0.70 & 0.72 & 0.84 & 0.50 & 0.73 & 1 & 0.90 & 1 & 0.88 & 1 \\ \cline{1-1}  & F1-score & 0.70 & 0.71 & 0.84 & 0.58 & 0.72 & 1 & 0.90 & 1 & 0.90 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Performance metrics for 10%, 20%, 30%, 40% and 50% testing data using Reference frame as *Ref and redundant frame as *Red for with and without segmentation. 3. The highest accuracy obtained in SVM, PCA-SVM and the proposed approach is 100% which occurs once in SVM and PCA-SVM and eight times using the proposed approach. 4. Another observation is made where it can be seen that using the redundant frame extraction method, the result is better when using without any segmentation while using reference frame it is better to use with segmentation. This shows that segmentation is more valid and reliable with a known parameter like ground truth than without any ground truth. Furthermore, this is an important aspect of clinical usage.