Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline snake algorithm

Chen C, Lu H, Huang Y (2002) Cell-based dual snake model: a new approach to extracting highly winding boundaries in the ultrasound images. Ultrasound in Med Biol 28: 1061–1073

Mignotte M, Meunier J, Tardif JC (2001) Endocardial boundary estimation and tracking in echocardiographic images using deformable templates and Markov random fields. Pattern Anal Appl 4(4): 256–271

Edwards GJ, Taylor CJ, Cootes TF (1998) Interpreting face images using active appearance models. In Proc Int’l Conf Automatic Face Gesture Recog, pp 300–305

Cheng J, Foo SW, Krishnan SM (2006) Watershed presegmented snake for boundary detection and tracking of LV in echocardiographic images. IEEE Trans Info Technol Biomed 10(2): 414–416

Chuang G, Kuo C (1996) Wavelet descriptor of planar curves: theory and applications. IEEE Trans Image Process 5: 56–70

Park J, Keller JM (2001) snakes on the watershed. IEEE Trans Pattern Anal Mach Intell 23(10): 1201–1205

Jacob M, Blu T, Unser M (2004) Efficient energies and algorithms for parametric snakes. IEEE Trans Image Process 13: 1231–1244

Noble JA, Boukerroui D (2006) Ultrasound image segmentation: a survey. IEEE Trans Med Imaging 25

Jacob G, Alison Noble J, Mulet-Parada M, Blake A (1999) Evaluating a robust contour tracker on echocardiographic sequences. Med Image Anal 3(1): 63–75

Malassiotis S, Strintzis MG (1999) Tracking the left ventricle in echocardiographic images by learning heart dynamics. IEEE Trans Med Imaging 18(3): 282–290

Mikic I, Krucinski S, Thomas JD (1998) Segmentation and tracking in echocardiographic sequences: Active contours guided by optical flow estimates. IEEE Trans Med Imaging 17(2): 274–284

Chalana V, Linker DT, Haynor DR, Kim Y (1996) A multiple active contour model for cardiac boundary detection on echocardiographic sequences. IEEE Trans Med Imaging 15: 290–298

Angelini ED, Laine AF, Takuma S, Holmes JW, Homma S (2001) LV volume quantification via spatiotemporal analysis of real-time 3-D echocardiography. IEEE Trans Med Imaging 20(6): 457–469

Comaniciu D, Zhou XS, Krishnan S (2004) Robust real-time myocardial border tracking for echocardiography: an information fusion approach. IEEE Trans Med Imaging 23: 849–860

Kass M, Witkin A, Terzopoulos D (1988) snakes: active contour models. Int J Comput Vis 1(4): 321–331

Mishra A, Dutta PK, Ghosh MK (2003) A GA based approach for boundary detection of left ventricle with echocardiographic image sequences. Image Vis Comput 21: 967–976

Mignotte M, Meunier J (2001) A multiscale optimization approach for the dynamic contour-based boundary detection issue. Comput Med Imaging Graph 25(3): 265–275

Mignotte M, Meunier J, Tardif J-C (2001) Endocardial boundary estimation and tracking in echocardiographic images using deformable template and markov random fields. Pattern Anal Appl 4(4): 256–271

Brigger P, Engel R, Unser M (1988) B-Spline snakes and a JAVA interface: an Intuitive tool for general contour outlining. ICIP 2: 277–281

Brigger P, Hoeg J, Unser M (2000) B-spline snakes: a flexible tool for parametric contour detection. IEEE Trans Image Process 9(9): 1484–1496

Wang Y, Teoh EK, Shen D (2001) Structure-adaptive B-snake for segmenting complex objects. In: Proceedings 2001 International Conference on image processing, vol 2, Issue, 7–10 Oct 2001, pp 769–772

Menet S, Saint-Marc P, Medioni G (1990) B-snakes: Implementation and application to stereo. In: Image Understanding Workshop. Sept., pp 720–726

Xu C, Prince JL (1998) Generalized gradient vector flow external forces for active contours. Signal Process Int J 71(2): 131–139

Wang M, Evans J, Hassebrook L, Knapp C (1996) A multistage, optimal active contour model. IEEE Trans Image Process 5: 1586–1591

Hill A, Taylor CJ (1997) Automatic landmark identification using a new method of non-rigid correspondence. In: Proc. Information Processing in Medical Imaging (IPMI’97). Springer, Berlin, pp 483–488

Flickner M, Sawhney H, Pryor D, Lotspiech J (1994) Intelligent interactive image outlining using spline snakes. In: 28th Asilomar Conf signals, systems, computers 1:731–735

Wang Y, Teoch EK (2006) Object contour extraction using adaptive B-snake model. J Math Imaging Vis 24(3): 295–306

Marsousi M, Eftekhari A, Alirezaie J (2008) Object contour extraction in medical images by fast adaptive B-Snake. 30th Annual Int Conf of the IEEE Eng in medicine and biology society, pp 3068–3071

Rosenfeld A (1984) Multiresolution image processing. Springer, New York

Liao CW, Medioni G (1995) Surface approximation of a cloud of 3D points. Graph Model Image Process 57(1): 67–74

Wei M, Zhou Y, Wan M (2004) A fast snake model based on non-linear diffusion for medical image segmentation. Comput Med Imaging Graph 28: 109–117

Wang Y, Teoh EK (2005) Dynamic B-snake model for complex objects segmentation. Image Vis Comput 23: 1029–1040

Leung CC, Chan CH, Chan FHY, Tsui WK (2004) B-spline snakes in two stages Pattern Recognition, 2004. ICPR 2004. In: Proceedings of the 17th International Conference on vol 1, Issue, 23–26 Aug. 2004, pp 568–571