# IVUS Image Segmentation Using Superpixel-Wise Fuzzy Clustering and Level Set Evolution
## 5 Discussion  
In this paper, we propose the SFCME-LSE method for the extraction of the MAB and LIB in IVUS images. Next, we analyze the method in detail from four aspects: The benefit of superpixel-wise fuzzy clustering for extracting ROIs, the reliability of the ROI assignment framework, the parameter selection, and the assessment of the strengths and weaknesses of the method. In Figure 9, we present clustering results of SFCME and of FCM with spatial information [26]. Due to the intensity inhomogeneity and large amounts of speckle noise invariably existing in ultrasound images, the results of pixel-wise fuzzy clustering appear discontinuous. The integration of SLIC superpixels improves the ability of clustering to group pixels from the same tissue into one ROI, which simplifies the assignment of ROIs. Moreover, SFCME takes approximately 0.69 s per frame in our environment, while the other method takes 2.32 s.  
Figure 8: Examples of the segmentation results on Dataset I (the first three rows) and Dataset II (the last two rows). The green dashed line, cyan dashed line, magenta solid line, and red solid line correspond to the manually annotated lumen-intima border (LIB), the manually annotated media-adventitia border (MAB), the auto-detected LIB, and the auto-detected MAB, respectively. Among different IVUS images, even the same tissue may present diverse gray levels. Some images are visually brighter, while others are darker. In our ROI assignment framework, we define indicators \(D_{g}\), \(D_{a}\), and \(D_{s}\) according to the relative grayscale or spatial information of regions in a single image, which contributes to the thresholds' adaptation on dark or bright images. The three indicators are all \(R_{on}\)-dependent, and \(D_{s}\) is also MAB-dependent. With the indicators' variation under the update of \(R_{on}\) and the MAB throughout the assignment procedure, some superior regional features are extracted in the image. To visually illustrate the effectiveness of these indicators, we recorded the \(D_{g}\), \(D_{a}\), and \(D_{s}\) of the ROIs in 30 frames from Dataset I, as well as their classifications (calcification, adventitia, soft plaque, lumen, or shadow). The statistical results are displayed graphically in Figure 10. It is obvious that the components are distributed at different locations in the metric space formed by the three indicators. The thresholds controlling the assignment, \(T_{a1}\sim T_{a4}\), \(T_{s}\), and \(T_{g1}\sim T_{g4}\), are determined according to the statistical results. Furthermore, to reduce assignment error, two sets of conditions are considered for calcification, adventitia, and soft plaque. One decision is more rigorous in terms of the intensity (\(D_{g}\), \(D_{a}\)), while the other is more rigorous in terms of the location (\(D_{s}\)), as illustrated in Section 3.3.3 12233. Note that the discrimination error between calcification and soft plaque does not affect the extraction of the boundary. Important parameters involved in SFCME-LSE are listed in Table 2. \(D_{c}\) determines a circular catheter zone \(R_{c}\) including the ring-down artifact and is usually 43 pixels in 40 MHz IVUS images. Figure 10: Plots of the indicators and attributions of ROIs when \(\theta_{alven}\leq T_{\theta}\) (**left**) and \(\theta_{alven}>T_{\theta}\) (**right**). Figure 9: Comparison of the clustering results from SFCME (the second column) and pixel-wise fuzzy c-means with spatial information (the third column). As guidewire artifacts touch \(R_{c}\), we believe that the maximum distance between them is \(T_{d}\). \(L_{out}\) is set to 23 pixels, ensuring that pixels within this thickness belong to the shadow left by the calcification. \(T_{\theta}\) is set to stop the update of the MAB, and \(T_{area}\) is set to terminate the assignment of the ROIs. By changing values of weights \(\mu\), \(\beta\), and \(\
u\), the contribution of each term in Equation (17) to the evolution of deformable contours will be altered.