|
D.Cremers, S.J.Osher, and S.Soatto, “Kernel density estimation and intrinsic alignment for shape priors in level set segmentation, ” International Journal of Computer Vision, vol.69, no.3, pp. 335–351, 2006
|
|
S.Dambreville, Y.Rathi, and A.Tannenbaum, “A framework for image segmentation using shape models and kernel space shape priors, ” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, no.8, pp. 1385-1399, 2008
|
|
F.Kasmin, A.Abdullah, and A. S.Prabuwono, “Ensembles of Normalization Techniques to Improve the Accuracy of Otsu Method, ” Applied Mathematical Sciences, vol.9, pp. 1565-1578, 2015
|
|
C.M.Li, C.Y.Kao, J.C.Gore, and Z.H.Ding, “Minimization of Region-Scalable Fitting Energy for Image Segmentation, ” IEEE Trans. Image Processing, vol.17, no.10, pp. 1940-1949, 2008
|
|
W.McIlhagga, “The Canny Edge Detector Revisited, ” International Journal of Computer Vision, vol.91, no.3, pp.251-261, 2011
|
|
M.Pereyra., H.Batatia, and S.McLaughlin, “Exploiting information geometry to improve the convergence of nonparametric active contours, ” IEEE Transactions on Image Processing, vol.24, no.3, pp. 836-845, 2015
|
|
X.J.Qin, X.L.Li, Y.Liu, H.B.Lu, and P.K.Yan, “Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation, ” IEEE Journal of Biomedical and Health Informatics, vol.18, no.5, pp. 1707-1716, 2014
|
|
M.Thakur, S.S.Meghwani, and H.Jalota, “A modified real coded genetic algorithm for constrained optimization Applied Mathematics and Computation, ” Elsevier, vol.235, pp. 292-317, 2014
|
|
B.Wang, X.B.Gao, J.Li, X.L.Li, D.Tao, D.C.Tao, “A level set method with shape priors by using locality preserving projections, ” Neurocomputing , vol.170, pp. 188-200, 2015
|
|
X.Yang, X.B.Gao, D.C.Tao, X.L.Li, J.Li, “An Efficient MRF Embedded Level Set Method for Image Segmentation,” IEEE Transactions on Image Processing,vol. 24, no.1, pp.9-21, 2015
|
|
Y.Yuan, C.J.He, “Adaptive active contours without edges, ” Mathematical and Computer Modelling, vol.55, pp. 1705-1721, 2012
|