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Jiang, \u201cA nonparametric shape prior constrained active contour model for segmentation of coronaries in CTA images,\u201d Computational and mathematical methods in medicine, vol.2014, no.1, April 2014.","DOI":"10.1155\/2014\/302805"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] T.F. Chan and L.A. Vese, \u201cActive contours without edges,\u201d IEEE Trans. Image Process., vol.10, no.2, pp.266-277, Jan. 2001.","DOI":"10.1109\/83.902291"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] A. Yezzi, A. Tsai, and A. Willsky, \u201cA fully global approach to image segmentation via coupled curve evolution equations,\u201d Journal of Visual Communication and Image Representation, vol.13, no.1-2, pp.195-216, March 2002.","DOI":"10.1006\/jvci.2001.0500"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] L. Wang, C. Li, Q. Sun, D. Xia, and C.-Y. Kao, \u201cActive contours driven by local and global intensity fitting energy with application to brain MR image segmentation,\u201d Computerized Medical Imaging and Graphics, vol.33, no.7, pp.520-531, June 2009.","DOI":"10.1016\/j.compmedimag.2009.04.010"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] J. An, M. Rousson, and C. Xu, \u201c\u03b3-convergence approximation to piecewise smooth medical image segmentation,\u201d Medical Image Computing and Computer-Assisted Intervention-MICCAI, vol.10, no.2, pp.495-502, 2007.","DOI":"10.1007\/978-3-540-75759-7_60"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] J. Piovano, M. Rousson, and T. Papadopoulo, \u201cEfficient segmentation of piecewise smooth images,\u201d in Scale Space and Variational Methods in Computer Vision, pp.709-720, May 2007.","DOI":"10.1007\/978-3-540-72823-8_61"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] Y. Yang, A. Tannenbaum, D. Giddens, and A. Stillman, \u201cAutomatic segmentation of coronary arteries using bayesian driven implicit surfaces,\u201d Proc. 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2007, pp.189-192, May 2007.","DOI":"10.1109\/ISBI.2007.356820"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] M.W.K. Law and A.C.S. Chung, \u201cWeighted local variance-based edge detection and its application to vascular segmentation in magnetic resonance angiography,\u201d IEEE Trans. Med. Imag., vol.26, no.9, pp.1224-1241, Oct. 2007.","DOI":"10.1109\/TMI.2007.903231"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] C. Li, C.-Y. Kao, J.C. Gore, and Z. Ding, \u201cImplicit active contours driven by local binary fitting energy,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.1-7, July 2007.","DOI":"10.1109\/CVPR.2007.383014"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] C. Li, C.-Y. Kao, J.C. Gore, and Z. Ding, \u201cMinimization of region-scalable fitting energy for image segmentation,\u201d IEEE Trans. Image Process., vol.17, no.10, pp.1940-1949, Nov. 2008.","DOI":"10.1109\/TIP.2008.2002304"},{"key":"14","unstructured":"[14] B. Mohr, S. Masood, and C. Plakas, \u201cAccurate lumen segmentation and stenosis detection and quantification in coronary CTA,\u201d Proc. Int. Conf. 3D Cardiovascular Imaging: A MICCAI Segmentation Challenge Workshop, 2012."},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] S. Lankton and A. Tannenbaum, \u201cLocalizing region-based active contours,\u201d IEEE Trans. Image Process., vol.17, no.11, pp.2029-2039, Dec. 2008.","DOI":"10.1109\/TIP.2008.2004611"},{"key":"16","unstructured":"[16] S. Lankton, A. Stillman, P. Raggi, and A.R. Tannenbaum, \u201cSoft plaque detection and automatic vessel segmentation,\u201d Proc. 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