Automatic Segmentation and Diagnosis Based on Multi-Scale Two-Stage Region Growing and Skeleton Extraction for Vessel Stenosis in Coronary Angiography

Abstract

Although great progress has been made in vessel segmentation, the existing methods still can not accurately segment small vessels. A novel vessel segmentation and automatic diagnosis in coronary angiography image was proposed. During vessel segmentation, a new vessel function based on Hessian matrix was put forward. Then the vessel contour was extracted by the dual-stage region growing with automatic selection of seed point. Next, the automatic diagnosis was realized by vessel skeleton extraction, skeleton point search and diameter measurement. The experimental results demonstrate that our proposed vessel segmentation can extract the main branch contour accurately and have a good effect on the enhancement and segmentation of small vessels. The automatic diagnosis of vessel stenosis is fast. With a relatively accurate diagnosis result, it can provide a good reference and quantitative basis for the final judgment of the doctor.