Segmentation Method Based on Fusion Algorithm for Coronary Angiograms

Aiming at weak contrast between the coronary arteries and the background, a new segmentation method based on fusion algorithm is proposed. Firstly, the coronary arteries are extracted by using the maximizing entropy segmentation method based on Top-hat. Then the coronary arteries are extracted again by using the maximizing entropy segmentation method based on Gaussian filter. Finally, the last segmentation result is the image obtained by fusing two extracted coronary arteries images. A lot of experiments indicate that the proposed method outperforms the maximizing entropy method based on not only Top-hat but also Gaussian filter about the small vessels extraction and background elimination. In addition, the method is indeed valuable for diagnosis and the quantitative analysis of vessels.