Abstract
A 3D+t description of the coronary tree is important for diagnosis of coronary artery disease and therapy planning. In this paper, we propose a method for finding 3D+t points on coronary artery tree given tracked 2D+t point locations in X-ray rotational angiography images. In order to cope with the ill-posedness of the problem, we use a bilinear model of ventricle as a spatio-temporal constraint on the nonrigid structure of the coronary artery. Based on an energy minimization formulation, we estimate i) bilinear model parameters, ii) global rigid transformation between model and X-ray coordinate systems, and iii) correspondences between 2D coronary artery points on X-ray images and 3D points on bilinear model. We validated the algorithm using a software coronary artery phantom.
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Baka, N., Metz, C.T., Schultz, C., Neefjes, L., van Geuns, R.J., Lelieveldt, B.P.F., Niessen, W.J., van Walsum, T., de Bruijne, M.: Statistical coronary motion models for 2D+t/3D registration of x-ray coronary angiography and CTA. Med. Image Anal. 17(6), 698–709 (2013)
Chen, S.Y.J., Carroll, J.D.: Kinematic and deformation analysis of 4-D coronary arterial trees reconstructed from cine angiograms. IEEE Trans. Med. Imaging 22(6), 710–721 (2003)
Chui, H., Rangarajan, A.: A feature registration framework using mixture models. In: IEEE Workshop MMBIA, pp. 190–197 (2000)
Goodall, C.: Procrustes methods in the statistical analysis of shape. J. R. Stat. Soc. Series B Stat. Methodol. 53(2), 285–339 (1991)
Grech, M., Debono, J., Xuereb, R.G., Fenech, A., Grech, V.: A comparison between dual axis rotational coronary angiography and conventional coronary angiography. Catheter. Cardiovasc. Interv. 80(4), 576–580 (2012)
Hoogendoorn, C., Duchateau, N., Sanchez-Quintana, D., Whitmarsh, T., Sukno, F.M., De Craene, M., Lekadir, K., Frangi, A.F.: A high-resolution atlas and statistical model of the human heart from multislice CT. IEEE Trans. Med. Imaging 32(1), 28–44 (2013)
Hoogendoorn, C., Sukno, F.M., Ordás, S., Frangi, A.F.: Bilinear models for spatio-temporal point distribution analysis. Int. J. Comput. Vis. 85(3), 237–252 (2009)
Jandt, U., Schäfer, D., Grass, M., Rasche, V.: Automatic generation of 3D coronary artery centerlines using rotational x-ray angiography. Med. Image Anal. 13(6), 846–858 (2009)
Liao, R., Luc, D., Sun, Y., Kirchberg, K.: 3-D reconstruction of the coronary artery tree from multiple views of a rotational x-ray angiography. Int. J. Cardiovasc. Imaging 26, 733–749 (2010)
Nichols, M., Townsend, N., Scarborough, P., Rayner, M.: Cardiovascular disease in europe: epidemiological update. Eur. Heart. J. 34(39), 3028–3034 (2013)
Segars, W.P., Sturgeon, G., Mendonca, S., Grimes, J., Tsui, B.M.W.: 4D XCAT phantom for multimodality imaging research. Med. Phys. 37(9), 4902–4915 (2010)
Tenenbaum, J.B., Freeman, W.T.: Separating style and content with bilinear models. Neural. Comput. 12(6), 1247–1283 (2000)
Yang, J., Wang, Y., Liu, Y., Tang, S., Chen, W.: Novel approach for 3-D reconstruction of coronary arteries from two uncalibrated angiographic images. IEEE Trans. Image Process. 18(7), 1563–1572 (2009)
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Çimen, S., Hoogendoorn, C., Morris, P.D., Gunn, J., Frangi, A.F. (2014). Reconstruction of Coronary Trees from 3DRA Using a 3D+t Statistical Cardiac Prior. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8674. Springer, Cham. https://doi.org/10.1007/978-3-319-10470-6_77
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DOI: https://doi.org/10.1007/978-3-319-10470-6_77
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