Three-Dimensional Reconstruction of Two-Dimensional Cardiovascular Angiography Image Sequences by Local Threshold Segmentation Algorithm

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.