A feature extraction and segmentation algorithm for cardiovascular calcification medical images

Abstract

Cardiovascular disease (CVD) is a common disease related to the heart and blood vessels. Due to the lack of research on the characteristics and effect of cardiovascular calcification on hemodialysis patients in China, it is almost impossible to accurately extract, segment, and measure the cardiovascular calcified regions from the cardiovascular calcification image. This article proposed an algorithm to extract and segment the calcified regions based on image characteristics. Firstly, the dome method was used to obtain the approximate region of calcification and the basic extraction and segmentation algorithm was used to preprocess the calcified region. Then, the region of calcification was enhanced using the image enhancement method before being further processed by the basic algorithm. After that, the preprocessed segmented image was compared back to the original image and only the initial grey value of the common area was kept in the original image. Finally, the basic segmentation algorithm was utilized again to process the original image before the threshold division and binarization being performed to obtain the final segmentation results. The results indicated that our method can segment the calcified region more accurately and thus more accurate distinguishment of the calcified regions from the non-calcified regions can be achieved.