## 2 Materials and Methods
### Dataset  
The dataset was created as a consequence of liver tumor segmentation, which was held in connection with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017. The liver images from a 3D CT image have been segmented and released. In the axial direction, pixel sizes range from 0.56 mm to 1.0 mm, and in the \(z\)-direction, they range from 0.45 mm to 6.0 mm. The number of slices per CT scan varies from 42 to 1026, and all slices were resized to 150 pixels in size. The segmented data are published in [23] and are not labeled. The data are diagnosed by the radiologist, and the following table describes the label for each case. Table 1 shows the diagnosis of the human radiologist for each volume. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Volume\#**} & **Radiologist** & \multirow{2}{*}{**Volume\#**} & **Radiologist** & \multirow{2}{*}{**Volume\#**} & **Radiologist** & \multirow{2}{*}{**Volume\#**} & **Radiologist** \\  & & **Label** & & **Label** & & **Label** & **Label** & **Label** \\ \hline
1 & malignant & 27 & malignant & 53 & malignant & 79 & malignant & 105 & benign \\
2 & malignant & 28 & malignant & 54 & Normal & 80 & malignant & 106 & benign \\
3 & malignant & 29 & malignant & 55 & malignant & 81 & malignant & 107 & malignant \\
4 & malignant & 30 & malignant & 56 & malignant & 82 & benign & 108 & malignant \\
5 & malignant & 31 & malignant & 57 & benign & 83 & malignant & 109 & malignant \\
6 & benign & 32 & malignant & 58 & benign & 84 & malignant & 110 & benign \\
7 & malignant & 33 & Normal & 59 & malignant & 85 & benign & 111 & malignant \\
8 & malignant & 34 & malignant & 60 & benign & 86 & benign & 112 & benign \\
9 & malignant & 35 & benign & 61 & malignant & 87 & malignant & 113 & benign \\
10 & malignant & 36 & malignant & 62 & benign & 88 & benign & 114 & malignant \\
11 & malignant & 37 & benign & 63 & benign & 89 & malignant & 115 & malignant \\
12 & malignant & 38 & malignant & 64 & benign & 90 & benign & 116 & malignant \\
13 & benign & 39 & Normal & 65 & malignant & 91 & benign & 117 & benign \\
14 & malignant & 40 & malignant & 66 & benign & 92 & malignant & 118 & malignant \\
15 & malignant & 41 & malignant & 67 & malignant & 93 & malignant & 119 & malignant \\
16 & benign & 42 & benign & 68 & malignant & 94 & malignant & 120 & malignant \\
17 & malignant & 43 & benign & 69 & malignant & 95 & malignant & 121 & benign \\
18 & malignant & 44 & benign & 70 & malignant & 96 & malignant & 122 & benign \\
19 & malignant & 45 & benign & 71 & malignant & 97 & malignant & 123 & benign \\
20 & malignant & 46 & malignant & 72 & benign & 98 & benign & 124 & malignant \\
21 & malignant & 47 & malignant & 73 & benign & 99 & malignant & 125 & malignant \\
22 & malignant & 48 & benign & 74 & malignant & 100 & malignant & 126 & malignant \\
23 & malignant & 49 & malignant & 75 & malignant & 101 & malignant & 127 & benign \\
24 & malignant & 50 & malignant & 76 & malignant & 102 & malignant & 128 & benign \\
25 & benign & 51 & benign & 77 & benign & 103 & malignant & 129 & malignant \\
26 & Normal & 52 & malignant & 78 & malignant & 104 & benign & 130 & malignant \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The diagnosis of liver CT volumes by Radiologist Diagnosis. Figure 1: The proposed method. The number of benign cases is 39, the number of malignant cases is 85, whereas 6 cases are diagnosed with no lesions, which means they are normal. The normal cases are excluded from the dataset because they are not sufficient for classification. The proposed method is just designed based on benign and malignant cases. Figure 2 describes the malignant liver slice, the segmented liver, and the 3D view of the liver. On the other hand, Figure 3 represents the benign case of the liver and its corresponding segment with its 3D view. The benign segmented liver is augmented with a scale [0.9-1] rotated [2\({}^{\circ}\)-5\({}^{\circ}\)].