Abstract

The study focused on the extraction of cardiovascular two-dimensional angiography sequences and the three-dimensional reconstruction based on the local threshold segmentation algorithm. Specifically, the two-dimensional cardiovascular angiography sequence was extracted first, and Gaussian smoothing was adopted for image preprocessing. Then, optimize maximum between-class variance (OSTU) was compared with the traditional two-dimensional OSTU and fast two-dimensional OSTU and applied in the segmentation of cardiovascular angiography images. It was found that the cardiovascular structure itself was continuous, the contrast agent diffused relatively evenly in the blood vessel, and the gray level of the blood vessel was also continuous. The degree of smoothness was consistent in all directions by Gaussian smoothing, avoiding the direction deviation of the smoothened image. The operation time (0.59 s) of the optimize OSTU was significantly shorter than that of traditional OSTU (35.68 s) and fast two-dimensional OSTU (6.34 s) ( P < 0.05 ). The local threshold segmentation algorithm can realize the continuous edge extraction of blood vessels and accurately reflect the stenosis of blood vessels. The results of blood vessel diameter measurement showed that the diameter from the end of blood vessel to the intersection varied linearly from 5.5 mm to 9.0 mm. In short, the optimize OSTU demonstrated good segmentation effects and fast calculation time; it successfully extracted continuous two-dimensional cardiovascular angiography images and can be used in three-dimensional reconstruction of cardiovascular images.

Highlights

  • With the continuous improvement of living standards, cardiovascular diseases have become the first killer threatening human health [1]

  • Compared with the global threshold segmentation algorithm, the local threshold segmentation algorithm lost less blood vessel information; the small and large blood vessels in the middle area were separated clearly without damage to the large blood vessel structure; and it can avoid the interference of light and contrast dose

  • As for extraction of edge of the blood vessel, the results showed that the extracted blood vessel edge was continuous, and the local edge can be optimized to remove the structural noise in the background [23]

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Summary

Introduction

With the continuous improvement of living standards, cardiovascular diseases have become the first killer threatening human health [1]. According to Report on Cardiovascular Health and Diseases in China 2019: An Updated Summary, the prevention and control of cardiovascular diseases in China is facing serious challenges, and there are estimated 330 million patients with cardiovascular diseases nationwide [2]. There are mainly two treatment methods for cardiovascular diseases: interventional method and image segmentation. Interventional treatment is direct and effective, but it increases the pain of patients [4]. Image segmentation can only provide two-dimensional image information, so it requires three-dimensional reconstruction of blood vessels, and its effectiveness remains to be evaluated [5]. Segmentation algorithm-based image analysis mainly includes X-ray images and ultrasound images. In the diagnosis and treatment of cardiovascular diseases, three-dimensional reconstruction can be performed on two-dimensional imaging sequences [6]

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