Multi-feature gradient vector flow snakes for adaptive segmentation of the ultrasound images of breast cancer
Tóm tắt
Từ khóa
Tài liệu tham khảo
Kass, 1988, Snakes: active contour models, International Journal of Computer Vision, 1, 321, 10.1007/BF00133570
Lefebvre, 1998, Automatic detection of the boundary of the calcaneus from ultrasound parametric images using an active contour model; clinical assessment, IEEE Transactions on Medical Imaging, 17, 45, 10.1109/42.668693
Y.S. Akgul, C. Kambhamettu, M. Stone, Extraction and tracking of the tongue surface from ultrasound image sequences, in: International IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Santa Barbara, California, 1998, pp. 298–303.
R. Chung, C.K. Ho, Using 2D active contour models for 3D reconstruction from serial sections, in: Proceedings of the 13th International IEEE Conference on Pattern Recognition, Vienna, Austria, 1996, pp. 849–853.
Fenster, 1998, Three-dimensional ultrasound imaging system for prostate cancer diagnosis and treatment, IEEE Transactions on Instrumentation and Measurement, 47, 1439, 10.1109/19.746709
Strintzis, 1997, Maximum likelihood motion estimation in ultrasound image sequences, IEEE Signal Processing Letters, 4, 156, 10.1109/97.586034
Chen, 2003, 3-D breast ultrasound segmentation using active contour model, Ultrasound in Medicine and Biology, 29, 1017, 10.1016/S0301-5629(03)00059-0
Chang, 2003, Segmentation of breast tumor in three-dimensional ultrasound images using three-dimensional discrete active contour model, Ultrasound in Medicine and Biology, 29, 1571, 10.1016/S0301-5629(03)00992-X
Cvancarova, 2005, Segmentation of ultrasound images of liver tumors applying snake algorithms and GVF, Congress Series, 1281, 218, 10.1016/j.ics.2005.03.190
Aleman-Flores, 2005, Computerized ultrasound characterization of breast tumors, International Congress Series, 1281, 1063, 10.1016/j.ics.2005.03.157
Cohen, 1991, On active contour models and balloon, CVGIP: Image Understanding, 53, 211, 10.1016/1049-9660(91)90028-N
Cohen, 1993, Finite-element methods for active contour models and balloons for 2-D and 3-D images, IEEE Transactions on Pattern Analysis and Machine Intelligence, 15, 1131, 10.1109/34.244675
Pujol, 2005, Fundamentals of stop and go active models, Image Vision and Computing, 23, 681, 10.1016/j.imavis.2005.03.007
Tang, 2009, A multi-direction GVF snake for the segmentation of skin cancer images, Pattern Recognition, 42, 1172, 10.1016/j.patcog.2008.09.007
Shih, 2007, Locating object contours in complex background using improved snakes, Computer Vision and Image Understanding, 105, 93, 10.1016/j.cviu.2006.08.007
Dagher, 2008, Waterballoons: a hybrid watershed balloon snake segmentation, Image Vision and Computing, 26, 905, 10.1016/j.imavis.2007.10.010
Zhu, 2011, A snake based method for segmentation of intravascular ultrasound images and its in vivo validation, Ultrasonics, 51, 181, 10.1016/j.ultras.2010.08.001
Fenster, 2001, Sectored snakes: evaluating learned energy segmentations, Transactions in Pattern Analysis and Machine Intelligence, 23, 1028, 10.1109/34.955115
Charmi, 2008, Fourier-based geometric shape prior for snakes, Pattern Recognition Letters, 29, 897, 10.1016/j.patrec.2008.01.011
Chesnaud, 1999, Statistical region snake-based segmentation adapted to different physical noise models, IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 1145, 10.1109/34.809108
Ronfard, 1994, Region-based strategies for active contour models, International Journal of Computer Vision, 13, 229, 10.1007/BF01427153
Zhu, 1996, Region competition: unifying snakes, region growing, and Bayes/MDL for multiband image segmentation, IEEE Transactions in Pattern Analysis and Machine Intelligence, 18, 884, 10.1109/34.537343
McInerney, 2000, T-snakes: topology adaptive snakes, Medical Image Analysis, 4, 73, 10.1016/S1361-8415(00)00008-6
Giraldi, 2003, Dual-T-snakes model for medical imaging segmentation, Pattern Recognition Letters, 24, 993, 10.1016/S0167-8655(02)00223-4
H. Delingnette, J. Montagnat, New algorithm for controlling active contours shape and topology, in: Sixth European Conference on Computer Vision (ECCV), Ireland, vol. 2, 2000, pp. 381–395.
Delingette, 2001, Shape and topology constraints on parametric active contours, Computer Vision and Image Understanding, 83, 140, 10.1006/cviu.2001.0920
Malladi, 1995, Shape modeling with front propagation, IEEE Transactions in Pattern Analysis and Machine Intelligence, 17, 158, 10.1109/34.368173
Osher, 1988, Fronts propagating with curvature dependent speed: algorithms based on Hamilton–Jacobi formulation, Journal of Computational Physics, 79, 12, 10.1016/0021-9991(88)90002-2
Caselles, 1997, Geodesic active contours, International Journal of Computer Vision, 22, 61, 10.1023/A:1007979827043
Siddiqi, 1998, Area and length minimizing flows for shape segmentation, IEEE Transactions in Image Processing, 7, 433, 10.1109/83.661193
Wang, 2004, Deformable contour method: a constrained optimization approach, International Journal of Computer Vision, 59, 87, 10.1023/B:VISI.0000020672.14006.ad
He, 2008, A comparative study of deformable contour methods on medical image segmentation, Image and Vision Computing, 26, 141, 10.1016/j.imavis.2007.07.010
Xu, 2000, Image segmentation using deformable models, vol. 2, 129
Li, 2005, Segmentation of external force field for automatic initialization and splitting of snakes, Pattern Recognition, 38, 1947, 10.1016/j.patcog.2004.12.015
Rochery, 2006, Higher order active contours, International Journal of Computer Vision, 69, 27, 10.1007/s11263-006-6851-y
Xu, 1998, Snakes, shapes, and gradient vector flow, IEEE Transaction on Image Processing, 7, 359, 10.1109/83.661186
Xu, 1997, Gradient vector flow: a new external force for snakes, Proceedings of the International IEEE Computer Society Conference on Computer Vision and, Pattern Recognition, 66
Xu, 1998, Generalized gradient vector flow external forces for active contours, Signal Processing, 71, 131, 10.1016/S0165-1684(98)00140-6
Wei, 2004, A fast snake model based on non-linear diffusion for medical image segmentation, Computerized Medical Imaging and Graphics, 28, 109, 10.1016/j.compmedimag.2003.12.002
Mille, 2009, Narrow band region-based active contours and surfaces for 2d and 3d segmentation, Computer Vision and Image Understanding, 113, 946, 10.1016/j.cviu.2009.05.002
Shang, 2008, Region competition based active contour for medical object extraction, Computerized Medical Imaging and Graphics, 32, 109, 10.1016/j.compmedimag.2007.10.004
Jumaat, 2010, Segmentation of masses from breast ultrasound images using parametric active contour algorithm, Procedia – Social and Behavioral Sciences, 8, 640, 10.1016/j.sbspro.2010.12.089
Chen, 2003, 3-D breast ultrasound segmentation using active contour model, Ultrasound in Medicine and Biology, 29, 1017, 10.1016/S0301-5629(03)00059-0
Chang, 2003, Segmentation of breast tumor in three-dimensional ultrasound images using three-dimensional discrete active contour model, Ultrasound in Medicine and Biology, 29, 1571, 10.1016/S0301-5629(03)00992-X
McInerney, 2008, Sketch-snakes: sketch-line initialized snakes for efficient interactive medical image segmentation, Computerized Medical Imaging and Graphics, 32, 331, 10.1016/j.compmedimag.2007.11.004
Hamarneh, 2000, Combining snakes and active shape models for segmenting the human left ventricle in echocardiographic images, Computers in Cardiology, 115
Chen, 2000, An early vision-based snake model for ultrasound image segmentation, Ultrasound in Medicine and Biology, 26, 273, 10.1016/S0301-5629(99)00140-4
Mignotte, 2001, A multiscale optimization approach for the dynamic contour-based boundary detection issue, Computerized Medical Imaging and Graphics, 25, 265, 10.1016/S0895-6111(00)00075-6
Rodtook, 2010, Continuous force field analysis for generalized gradient vector flow field, Pattern Recognition, 43, 3522, 10.1016/j.patcog.2010.04.003
Cheng, 2010, Automated breast cancer detection and classification using ultrasound images: a survey, Pattern Recognition, 43, 299, 10.1016/j.patcog.2009.05.012
Lee, 1980, Digital image enhancement and noise filtering by using local statistics, IEEE Transactions in Pattern Analysis and, Machine Intelligence, PAM1-2, 165, 10.1109/TPAMI.1980.4766994
Frost, 1982, A model for radar images and its application to adaptive digital filtering of multiplicative noise, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-4, 157, 10.1109/TPAMI.1982.4767223
Kuan, 1987, Adaptive restoration of images with speckle, IEEE on Transactions Acoustic, Speech and, Signal Processing, ASSP-35, 373, 10.1109/TASSP.1987.1165131
Gupta, 2007, A versatile technique for visual enhancement of medical ultrasound images, Digital Signal Processing, 17, 542, 10.1016/j.dsp.2006.12.001
Zhang, 2007, Boundary delineation in transrectal ultrasound image for prostate cancer, Computers in Biology and Medicine, 37, 1591, 10.1016/j.compbiomed.2007.02.008
Liu, 2010, Probability density difference-based active contour for ultrasound image segmentation, Pattern Recognition, 43, 2028, 10.1016/j.patcog.2010.01.002
Perona, 1990, Scale-space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12, 629, 10.1109/34.56205
Czerwinski, 1999, Detection of lines and boundaries in speckle images – application to medical ultrasound, IEEE Transactions on Medical Imaging, 18, 126, 10.1109/42.759114
Lopes, 1990, Adaptive speckle filters and scene heterogeneity, IEEE Transactions on Geoscience and Remote Sensing, 28, 992, 10.1109/36.62623
Huang, 2007, Level set contouring for breast tumor in sonography, Journal of Digital Imaging, 20, 238, 10.1007/s10278-006-1041-6
Levienaise-Obadia, 1999, Adaptive segmentation of ultrasound images, Image Vision and Computing, 17, 583, 10.1016/S0262-8856(98)00177-2
Yu, 2009, Object density-based image segmentation and its applications in biomedical image analysis, Computer Methods and Programs in Biomedicine, 96, 193, 10.1016/j.cmpb.2009.04.013
Vincent, 1993, Morphological grayscale reconstruction in image analysis Applications and efficient algorithms, IEEE Transactions on Image Processing, 2, 176, 10.1109/83.217222
Mignotte, 2001, A multiscale optimization approach for the dynamic contour-based boundary detection issue, Computerized Medical Imaging and Graphics, 25, 265, 10.1016/S0895-6111(00)00075-6
Ray, 2001, A fast and flexible multiresolution snake with a definite termination criterion, Pattern Recognition, 34, 1483, 10.1016/S0031-3203(00)00077-7
Chucherd, 2010, Phase portrait analysis for multiresolution generalized gradient vector flow, IEICE Transactions on Information and Systems, E93-D, 2822, 10.1587/transinf.E93.D.2822
Fritsch, 1980, Monotone piecewise cubic interpolation, SIAM Journal of Numerical Analysis, 17, 238, 10.1137/0717021
Castelmen, 1996
Chipman, 2006, Hybrid hierarchical clustering with applications to microarray data, Biostatistics, 2, 286
Naldi, 2002, Relaxation schemes for PDEs and applications to fourth order diffusion equations, Surveys on Mathematics for Industry, 10, 315
Hsu, 2008, Automatic segmentation of liver PET images, Computerized Medical Imaging and Graphics, 32, 601, 10.1016/j.compmedimag.2008.07.001
C.Y. Hsu, S.H. Chen, K.L. Wang, Active contour model with a novel image force field, in: Proceeding of the Conference CVGIP-2003, Taiwan, 2003, pp. 477–483.
Hsu, 2012, Automatic extraction of face contours in images and videos, Future Generation Computer Systems, 28, 322, 10.1016/j.future.2010.11.008
Ghita, 2010, A new GVF-based image enhancement formulation for use in the presence of mixed noise, Pattern Recognition, 43, 2646, 10.1016/j.patcog.2010.02.023
Li, 2007, Active contour external force using vector field convolution for image Segmentation, IEEE Transactions on Inage Processing, 16, 2096, 10.1109/TIP.2007.899601
Park, 2001, Active contour model with gradient directional information: Directional snake, IEEE Transactions in Circuits and Systems for Video Technology, 11, 252, 10.1109/76.905991
Cheng, 2006, Dynamic directional gradient vector flow for snakes, IEEE Transactions on Image Processing, 15, 1563, 10.1109/TIP.2006.871140
M.-P. Dubuisson, A.K. Jain, A modified Hausdorff distance for object matching proceedings, in: International Conference on Pattern Recognition, Israel, 1994, pp. 566–568.
Mumford, 1989, Optimal approximation by piecewise smooth functions and associated variational problems, Communications on Pure Applied Mathematics, 42, 577, 10.1002/cpa.3160420503
Vitti, 2012, The Mumford–Shah variational model for image segmentation: an overview of the theory, implementation and use, ISPRS Journal of Photogrammetry and Remote Sensing, 69, 50, 10.1016/j.isprsjprs.2012.02.005
Vese, 2002, A multiphase level set framework for image segmentation using the Mumford and Shah model, International Journal of Computer Vision, 50, 271, 10.1023/A:1020874308076
Yuan, 2012, Adaptive active contours without edges, Mathematical and Computer Modeling, 55, 1705, 10.1016/j.mcm.2011.11.014
L. Chan-Fei1, W. Yao-Nanm, L. Guo-Cai, A new splitting active contour framework based on Chan–Vese piecewise smooth model, Acta Automatica Sinica 34 (6) (2008) 660–664.
Diop, 2013, Bi-planar image segmentation based on variational geometrical active contours with shape priors, Medical Image Analysis, 17, 165, 10.1016/j.media.2012.09.006
Jain, 1996, Object matching using deformable templates, IEEE Transactions on Pattern Analysis and Machine Intelligence, 18, 267, 10.1109/34.485555
<http://www.queensirikitcentreforbreastcancer.com/en/our_team.php>.