# Computer Aided Detection of Pulmonary Embolism Using Multi-Slice Multi-Axial Segmentation
## 3 Results  
First, we evaluated the segmentation performance of the proposed method. Qualitative segmentation results are shown in Figure 3, where green labels represent true positives, red labels false negatives, and yellow labels false positives. The average per-scan segmentation Dice score was 0.485 (standard deviation of 0.297) for the \(2D\) network, 0.367 (standard deviation of 0.214) for the \(2.5D\) network, and 0.296 (standard deviation of 0.160) for the \(3D\) network. In all the cases, the standard deviation showed large discrepancies across scans. Figure A1 shows the relationships between the total size of the embol in the scan, measured in voxels, and the Dice coefficient. There was a clear trend where the larger was the emboli in the scan, the better was the segmentation. Table 1 shows the per embolus sensitivity of each of the three methods and the number of false positives per scan for the three tolerance margins \(\epsilon\) = 0 mm, \(\epsilon\) = 2 mm, and \(\epsilon\) = 5 mm. The threshold to set the operating point of the method was set at 0.75. There was a clear improvement of the \(2.5D\) method over the \(2D\) method. For \(\epsilon\) = 0 mm and \(\epsilon\) = 2 mm, the sensitivity was similar, but the number of False Positives per Scan (FPS) was more than halved. For \(\epsilon\) = 5 mm, there was an increase in sensitivity paired with a decrease in the number of FPS. The data in the table show no clear improvement between the \(2.5D\) and \(3D\) methods. The \(3D\) method had higher sensitivity, but also a higher number of FPS. Figure 4 displays the FROC curves. We included the results of the CAD-PE challenge in these images challenge to enable comparison [14,18]. We refer the reader to these references for a description and thorough evaluation of the other methods. The _ASU-Mayo_ method is best described in [15] and \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \(\epsilon\) = 0 mm & \(\epsilon\) = 2 mm & \(\epsilon\) = 5 mm \\ \hline
**Method** & **Sens** & **FPS** & **Sens** & **FPS** & **Sens** & **FPS** \\ \hline \(2D\) & 0.49 & 1.5 & 0.56 & 1.45 & 0.59 & 1.35 \\ \(2.5D\) & 0.48 & 0.65 & 0.54 & 0.55 & 0.63 & 0.50 \\ \(3D\) & 0.55 & 1.00 & 0.61 & 1.00 & 0.68 & 0.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Per embolus sensitivity and false positives per scan of the three proposed methods at the three tolerance levels. The cutoff threshold was set at 0.75. Figure 3: Network outputs after thresholding and closing operations compared to the reference standard segmentation with \(\epsilon\) = 0 mm. True positives are shown in green, false positives in yellow, and false negative in red. A predicted clot coordinate for that slice level is represented as a red cross. the _FUM-Mvlab_ method in [22]. The x-axis scale changes between the left and the right columns. Please note that most methods do not detect all emboli, since they are not part of their candidate selection mechanism or the segmentations did not reach the 0.5 threshold. The three proposed methods outperformed the other participants of the CAD-PE challenge for all the regimes of FPS. The 2.5\(D\) and 3\(D\) methods outperformed the 2\(D\) method for all the regimes of FPS in which they have data. There was a small increase in sensitivity of the 2.5\(D\) method over the 3\(D\) method in the range [0.25-4] FPS. The 3\(D\) method clearly outperformed the 2.5\(D\) method on the range [0-0.25] FPS. The performance of the three proposed methods with respect to embolus volume is shown in Figure 5. Each sub-image displays the histogram of embolus volume in green and the amount of  
Figure 4: Free-response Receiver Operating Characteristic (FROC) curves of the different methods proposed in this work, together with the results of other methods submitted to the Computer Aided Detection of Pulmonary Embolism (CAD-PE) challenge [14], using \(\epsilon\) of 0, 2, and 5 mm. The x-axis represents the false positive rate per scan and the y-axis is the per embolus sensitivity.