# Spider U-Net: Incorporating Inter-Slice Connectivity Using LSTM for 3D Blood Vessel Segmentation
## 4 Results  
We report the performances of the Spider U-Net and the other comparative models on test set of three datasets. Average dice coefficient score (DSC) and Intersection-over-union (IoU) were the evaluation metrics for all experiments.
intersection-over-union (IoU). Detailed results are shown in Table 2. Spider U-Net achieved the best performance among all models except for IoU on the brain MRA dataset. Qualitative results are shown in Figure 4. Yellow, red, and blue colors denote true-positive, false-positive, and false-negative each.  
For the brain MRA dataset, 2D U-Net, 3D U-Net, FCN-RNN, and Spider U-Net scored 0.745, 0.716, 0.752, and 0.793 for DSC and 0.673, 0.617, 0.758, and 0.743 for IoU, respectively. As an example, in the first row in Figure 4, entire models failed to successfully predict the posterior cerebral arteries located on the bottom side but could predict relatively thick vessels such as the internal carotid artery and basilar artery. Only Spider U-Net predicted all four visible anterior cerebral arteries which are the thinnest vessel type.  
For the abdomen CT dataset, 2D U-Net, 3D U-Net, FCN-RNN, and Spider U-Net achieved 0.327, 0.145, 0.351, and 0.456 for DSC and 0.277, 0.152, 0.271, and 0.375 for IoU, respectively. An example of hepatic vessel segmentation in the second row in Figure 4 shows  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Metric** & **Dataset** & **2D U-Net** & **3D U-Net** & **FCN-RNN** & **Spider U-Net** \\ \hline \multirow{3}{*}{DSC} & Brain MRA & 0.745 & 0.716 & 0.752 & 0.793 \\  & Abdomen CT & 0.327 & 0.145 & 0.351 & 0.456 \\  & Cardiac MRI & 0.772 & 0.726 & 0.812 & 0.833 \\ \hline \multirow{3}{*}{IoU} & Brain MRA & 0.673 & 0.617 & 0.758 & 0.743 \\  & Abdomen CT & 0.277 & 0.152 & 0.271 & 0.375 \\ \cline{1-1}  & Cardiac MRI & 0.681 & 0.624 & 0.707 & 0.728 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Average of the dice score (DSC) and intersection-over-union (IoU) of Spider U-Net and the other comparative models on three datasets.  
Figure 4: Qualitative results of Spider U-Net and the other comparative models on three datasets. The first row shows the brain MRA, the second row shows the abdomen CT, and the last row shows the cardiac MRI. The last row shows a single pulse of the left ventricle wall over 20 frames. As the cardiac MRI is 4D data, i.e., volume with the time axis, we visualized the cross-section of the left ventricle wall through central coronal plane. Each average value of dice coefficient score (DSC) and intersection-over-union (IoU) according to an example case is reported with DSC1 IoU. True-positive, false-positive, and false-negative are denoted as yellow, red, and blue, respectively.  
clear qualitative differences between Spider U-Net and the others. Spider U-Net produces less false-negative pixels, thus maintaining overall performance. On the other hand, Spider U-Net predicted a part of the vertebra as a blood vessel, producing a lot of false-positive pixels at the left side of the figure. To be utilized in real clinical scenarios, additional image processing techniques such as removing bone areas in the pre-processing stage and deleting the out-of-context blobs in the post-processing stage would be required. The performances of 3D U-Net are very poor, and we believe this is because of the anisotropy of the abdomen CT dataset discussed in Section 5.2.  
For the cardiac MRI dataset, 2D U-Net, 3D U-Net, FCN-RNN, and Spider U-Net scored 0.882, 0.822, 0.877, and 0.891 for DSC, and 0.790, 0.704, 0.782, and 0.804 for IoU, respectively. The third row in Figure 4 represents qualitative examples of cardiac MRI predictions. As this dataset is given in 4D, i.e., 20 frames of 3D cardiac volume representing a single cardiac cycle, we consecutively arranged a cross-section view of 20 frames of volumes through the central coronal plane.