Blood Vessel Segmentation Based on Digital Subtraction Angiography Sequence
Yan Zhang, Huiqin Jiang, Ling Ma · 2018
In order to extract cerebrovascular vessels in Digital Subtraction Angiography sequence and improve the diagnosis accuracy, we propose a method of precise segmentation of blood vessels based on DSA sequence. Firstly, we used the piece-wise linear transformation for adjusting the grayscale and the multi-scale Hessian matrix for enhancing the overall image. Secondly, we design an algorithm using the gradient of the vascular edge to strengthen the edge. Third, we use morphological methods to eliminate the noise around the blood vessels. Finally, we segment the blood vessels and fuse the blood vessels of each frame with the weighted method to get a more comprehensive blood vessel architecture. The main contribution is to accurately segment the single-frame blood vessel information through the enhancement of blood vessel edges and noise removal, and to fuse every frame information to obtain more comprehensive blood vessels. Experimental results show that the proposed method can segment blood vessels more accurately. The result has a good visual diagnostic quality.