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Detection of narrowed coronary arteries in X-ray Angiographic images using contour processing of segmented Heart Vessels based on Hessian Vesselness Filter and Wavelet Based Image Fusion
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 36 - Number 9 |
| Year of Publication: 2011 |
| Authors: M. J. Rastegar Fatemi, Seyed Mostafa Mirhassani, Elham Ghasemi |
10.5120/4520-6416
|
M. J. Rastegar Fatemi, Seyed Mostafa Mirhassani, Elham Ghasemi . Detection of narrowed coronary arteries in X-ray Angiographic images using contour processing of segmented Heart Vessels based on Hessian Vesselness Filter and Wavelet Based Image Fusion. International Journal of Computer Applications. 36, 9 ( December 2011), 27-33. DOI=10.5120/4520-6416
Abstract
In this paper a method for Detection of narrowed coronary arteries in X-ray Angiographic images is addressed. For this purpose firstly coronary arteries are segmented base on some probability masks which indicates the membership function of being a vessel for each pixel in the image. In order to build the membership functions whole of angiographic frames in the sequence are utilized. To this aim, angiographic sequence is filtered by the Hessian based vesselness filter to increase discrimination between the vascular structures and the background. Next, a 2D discrete wavelet transform is employed for fusion of the angiographic frames and their filtered versions. In the next step, the heart vessels are detected by applying the fused image with a couple of constant values as threshold coefficients. The coefficients are employed to adjust the effect of threshold. As a consequence, two images containing the detected vessels are yielded. After that, in order to mask out the redundant particles in the result morphological operations are employed. In order to find narrowed vessels their contours are obtained and the thickness of vessels is measured. A predefined threshold is employed to find the abrupt decrease in the vessel thickness. Experiments demonstrate the efficiency of the proposed method in order to detect the narrowed heart vessels in X-ray angiographic frames.
References
- Wink, O., et al. 2002. 3D MRA coronary axis determination using a minimum cost approach, Magnetic Resonance in Medicine. 47 (6) 1169– 1175.
- Aylward, S.R., Bullit E. 2002. Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction, IEEE Transactions on Medical Imaging, 21 (2) 61–75.
- Lorenz, C., et al. 1997. Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D and 3D medical images, CRVMed-MRCAS Proceedings, Springer Verlag, 233– 242.
- Sato, Y., et al. 1998. 3-D multi-scale line filter for segmentation and visualization of curvilinear structures in medical images, Medical Image Analysis 2 (2) 143– 168.
- Frangi, A.F., et al., 1998. Multiscale vessel enhancement filtering, MICCAI Proceedings, Springer Verlag.
- Yim P.J. et al., 2001. Vessel surface reconstruction with a tubular deformable model, IEEE Transactions on Medical Imaging, 20 (12) 1411– 1421.
- Krissian, K., Malandain, G., Ayache, N., Vaillant, R., Trousset, Y., 2000. Model-based detection of tubular structures in 3D images. Computer Vision and Image Understanding, 80 (2), 130–171.
- Lewis, J. J., Robert, J., O’Callaghan, S., Nikolov G., Bull, D. R., Canagarajah, N., 2007. Pixel- and region-based image fusion with complex wavelets, Journal of Information Fusion, Elsevier, 8 (2), April 2007, 119-130.
- Chareontam, O., Patanavijit, V., Jtapunkul, S., 2006. A Robust Region-Based Multiscale Image Fusion Scheme for Mis-Registration Problem of Thermal and Visible Images ,8th International Conference on Pattern Recognition (ICPR'06) 3, 2006, 669-672.
- Mirhassani, S.M., Hosseini, M.M., Behrad A., 2009. Improvement of Hessian Based Vessel Segmentation Using two Stage Threshold and Morphological Image Recovering, International Conference on Innovations in Information Technology, (IIT '09), (Dec. 2009), 1 50-54.
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