IVUS Image Segmentation Using Superpixel-Wise Fuzzy Clustering and Level Set Evolution

Xia Xia,Wang Wang,Zhou Zhou,Guo Guo,Yan Yan,Huang Huang

doi:10.3390/app9224967

Abstract

Reliable detection of the media-adventitia border (MAB) and the lumen-intima border (LIB) in intravascular ultrasound (IVUS) images remains a challenging task that is of high clinical interest. In this paper, we propose a superpixel-wise fuzzy clustering technique modified by edges, followed by level set evolution (SFCME-LSE), for automatic border extraction in 40 MHz IVUS images. The contributions are three-fold. First, the usage of superpixels suppresses the influence of speckle noise in ultrasound images on the clustering results. Second, we propose a region of interest (ROI) assignment scheme to prevent the segmentation from being distracted by pathological structures and artifacts. Finally, the contour is converged towards the target boundary through LSE with an appropriately improved edge indicator. Quantitative evaluations on two IVUS datasets by the Jaccard measure (JM), the percentage of area difference (PAD), and the Hausdorff distance (HD) demonstrate the effectiveness of the proposed SFCME-LSE method. SFCME-LSE achieves the minimal HD of 1.20 ± 0.66 mm and 1.18 ± 0.70 mm for the MAB and LIB, respectively, among several state-of-the-art methods on a publicly available dataset.

Highlights

Atherosclerosis involves pathological structures within the arterial wall, leading to a significant reduction in blood flow
We propose an automatic algorithm that assigns region of interest (ROI) in B1 and B2o to five categories: Calcification, adventitia, soft plaque, lumen, and shadow
The imaging system used for the acquisition is an iLab intravascular ultrasound (IVUS) (Boston Scientific, Fremont, United States) equipped with a 40 MHz OptiCross catheter

Summary

Introduction

Atherosclerosis involves pathological structures (stenosis, vulnerable plaque, etc.) within the arterial wall, leading to a significant reduction in blood flow. Atherosclerotic plaque can become fragile, potentially leading to cardiovascular diseases, such as angina, myocardial infarction, stroke, and sudden cardiac death [1]. Intravascular ultrasound (IVUS) is an in-vivo medical imaging technique capable of providing tomographic grayscale images of the vessel in real-time [2]. IVUS is commonly used in the diagnosis of atherosclerosis. Two types of borders in IVUS images, the lumen-intima border (LIB) and the media-adventitia border (MAB), are of substantial clinical interest. Automatic identification of these two borders is crucial for assessing the plaque burden and mechanical properties of the coronary artery [2]

Methods

Results

Conclusion