Zahra Turani - Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran
Reza A. Zoroofi - Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran,
Shapoor Shirani - Department of Radiology, School of Medicine, Tehran University of Medical Science
Sara Abkhofte - Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran

Nowadays cardiovascular diseases are one of the most major causes of mortality. Computed Tomography Angiography (CTA) is a very useful imaging tool for cardiovascular disease diagnosis. So it is important to analyze CTA images well. This paper proposed a new method for fully automatic cardiovascular segmentation based on combination of Hough transform and region growing algorithm. It is a robust method which segments ascending aorta, descending aorta, and left ventricle concurrently. Comparing to the manual method which is done by cardiologist and previous automatic and semi- automatic works, our method is faster, more accurate, and fully automatic. This procedure also can be applied to coronary segmentation. The validation of the acquired cardiovascular images is evaluated by a cardiologist. By evaluating 10 datasets, which contain about 5000 images, the accuracy of the method is 97.3% comparing to the gold standard. Our gold standard is the images segmented by cardiologist. In addition, average elapsed time is 0.18s per image.

Automatic cardiovascular segmentation, Computed Tomography Angiography, Hough transform, cardiovascular disease, region growing