Automatic extraction of coronary vessels from digital subtraction angiography

Songyuan Tang; Junhai Wen; Yongtian Wang; Yan-wei Chen

doi:10.1117/12.708749

22 March 2007 Automatic extraction of coronary vessels from digital subtraction angiography

Songyuan Tang, Junhai Wen, Yongtian Wang, Yan-wei Chen

Proceedings Volume 6509, Medical Imaging 2007: Visualization and Image-Guided Procedures; 65092A (2007) https://doi.org/10.1117/12.708749
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

In the X-ray coronary digital subtraction angiography, there are serious motion artifacts and noises, and backgrounds such as ribs, spine, cathers and etc, which are tube structures and like vessels. It's difficult to separate vessels from the background automatically if they are close each other. In this paper, an automatic extraction of coronary vessels from X-ray digital subtraction angiography is proposed. We used edge preserving smooth filter to reduce the noises in the images and keep the vessel edge firstly. Then affine and B-spline based FFD nonrigid registration is applied to the images. Compared with the segmentation method, the proposed method can remove background greatly and extract the coronary vessel very well.

Citation Download Citation

Songyuan Tang, Junhai Wen, Yongtian Wang, and Yan-wei Chen "Automatic extraction of coronary vessels from digital subtraction angiography", Proc. SPIE 6509, Medical Imaging 2007: Visualization and Image-Guided Procedures, 65092A (22 March 2007); https://doi.org/10.1117/12.708749

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available