Fast semi-automatic segmentation of focal liver lesions in contrast-enhanced ultrasound, based on a probabilistic model

References

• Bakas S, Chatzimichail K, Hoppe A, Galariotis V, Hunter G, Makris D. 2012. Histogram-based motion segmentation and characterisation of focal liver lesions in CEUS. Ann Br Mach Vision Assoc. 2012(7):1–14.
   Google Scholar
• Bakas S, Hoppe A, Chatzimichail K, Galariotis V, Hunter G, Makris D. 2012. Focal liver lesion tracking in CEUS for characterisation based on dynamic behaviour. Adv Visual Comput, Springer Berlin Heidelberg, Lecture Notes in Computer Science 7431:32–41. doi:10.1007/978-3-642-33179-4_4.
   Google Scholar
• Bakas S, Hunter G, Makris D, Thiebaud C. 2013. Spot the best frame: towards intelligent automated selection of the optimal frame for initialisation of focal liver lesion candidates in contrast-enhanced ultrasound video sequences. Proceedings of the 9th International Conference on Intelligent Environments, Athens, Greece. IEEE. p. 196–203. doi:10.1109/IE.2013.20.
   Google Scholar
• Bakas S, Labbé B, Hunter GJA, Sidhu PS, Chatzimichail K, Makris D. 2014. Fast segmentation of focal liver lesions in contrast-enhanced ultrasound data. Proceedings of Medical Image Understanding and Analysis, London, UK. City University. p. 73–78. doi:10.13140/2.1.1769.0400.
   Google Scholar
• Bakas S, Sidhu PS, Sellars ME, Hunter GJA, Makris D, Chatzimichail K. 2014. Non-invasive offline characterisation of contrast-enhanced ultrasound evaluations of focal liver lesions: dynamic assessment using a new tracking method. 20th European Congress of Radiology, Vienna, Austria. doi:10.1594/ecr2014/C-1378.
   Google Scholar
• Blachier M, Leleu H, Peck-Radosavljevic M, Valla DC, Roudot-Thoraval F. 2013. The burden of liver disease in Europe: a review of available epidemiological data. J Hepatol. 58(3):593–608.10.1016/j.jhep.2012.12.005.
   Google Scholar
• Claudon M, Dietrich CF, Choi BI, Cosgrove DO, Kudo M, Nolsøe CP, Piscaglia F, Wilson SR, Barr RG, Chammas MC, et al. 2013. Guidelines and good clinical practice recommendations for contrast enhanced ultrasound (CEUS) in the Liver – update 2012. Ultrasound Med Biol. 39(2):187–210. doi:10.1016/j.ultrasmedbio.2012.09.002.
   PubMed Web of Science ®Google Scholar
• Cootes TF, Taylor CJ. 1992. Active shape models-‘smart snakes’. Br Mach Vision Conf:266–275.
   Google Scholar
• Goertz RS, Bernatik T, Strobel D, Hahn EG, Haendl T. 2010. Software-based quantification of contrast-enhanced ultrasound in focal liver lesions – a feasibility study. Eur J Radiol. 75(2):e22–e26. doi:10.1016/j.ejrad.2009.11.004.
   PubMed Web of Science ®Google Scholar
• Huang-Wei C, Bleuzen A, Bourlier P, Roumy J, Bouakaz A, Pourcelot L, Tranquart F. 2006. Differential diagnosis of focal nodular hyperplasia with quantitative parametric analysis in contrast-enhanced sonography. Invest Radiol. 41(3):363–368. doi:10.1097/01.rli.0000195835.56589.55.
   PubMed Web of Science ®Google Scholar
• Kass M, Witkin A, Terzopoulos D. 1988. Snakes: active contour models. Int J Comput Vision. 1(4):321–331. doi:10.1007/BF00133570.
   Web of Science ®Google Scholar
• Lencioni R, Della Pina C, Crocetti L, Bozzi E, Cioni D. 2007. Clinical management of focal liver lesions: the key role of real-time contrast-enhanced US. Eur Radiol Suppl. 17(S6):73–79. doi:10.1007/s10406-007-0231-8.
   PubMed Web of Science ®Google Scholar
• Li C, Xu C, Gui C, Fox MD. 2010. Distance regularized level set evolution and its application to image segmentation. IEEE Trans Image Process. 19(12):3243–3254. doi:10.1109/TIP.2010.2069690.
   PubMed Web of Science ®Google Scholar
• Llovet JM, Burroughs A, Bruix J. 2003. Hepatocellular carcinoma. Lancet. 362(9399):1907–1917. doi:10.1016/S0140-6736(03)14964-1.
   PubMed Web of Science ®Google Scholar
• Marsousi M, Alirezaie J, Ahmadian A, Kocharian A. 2010. Segmenting echocardiography images using B-spline snake and active ellipse model. Eng Med Biol Soc Ann Int Confer IEEE, p. 3125–3128.
   Google Scholar
• Rognin N, Campos R, Thiran JP, Messager T, Broillet A, Frinking P, Mercier L, Arditi M. 2006. A new approach for automatic motion compensation for improved estimation of perfusion quantification parameters in ultrasound imaging. In: Proceedings of the Eighth French Conference on Acoustics. Tours (France): Société Française d'Acoustique. p. 61–65.
   Google Scholar
• Schneider M. 1999. Characteristics of SonoVue™. Echocardiography. 16(s1):743–746. doi:10.1111/j.1540-8175.1999.tb00144.x.
   PubMed Web of Science ®Google Scholar
• Strobel D, Seitz K, Blank W, Schuler A, Dietrich C, von Herbay A, Friedrich-Rust M, Bernatik T. 2009. Tumor-specific vascularization pattern of liver metastasis, hepatocellular carcinoma, hemangioma and focal nodular hyperplasia in the differential diagnosis of 1349 liver lesions in contrast-enhanced ultrasound (CEUS). Ultraschall in der Medizin. 30(4):376–382. doi:10.1055/s-0028-1109672.
   PubMed Web of Science ®Google Scholar
• Ta CN, Kono Y, Barback CV, Mattrey RF, Kummel AC. 2012. Automating tumor classification with pixel-by-pixel contrast-enhanced ultrasound perfusion kinetics. J Vac Sci Technol B. 30(2):02C103.
   Web of Science ®Google Scholar
• Westwood M, Joore M, Grutters J, Redekop K, Armstrong N, Lee K, Gloy V, Raatz H, Misso K, Severens J, et al. 2013. Contrast-enhanced ultrasound using SonoVue® (sulphur hexafluoride microbubbles) compared with contrast-enhanced computed tomography and contrast-enhanced magnetic resonance imaging for the characterisation of focal liver lesions and detection of liver metastases: a systematic review and cost-effectiveness analysis. Health Technol Assess. 17(16). doi:10.3310/hta17160.
   Web of Science ®Google Scholar
• Wilson SR, Burns PN. 2010. Microbubble-enhanced US in body imaging: what role? Radiology. 257(1):24–39. doi:10.1148/radiol.10091210.
   PubMed Web of Science ®Google Scholar
• World Health Organisation W.H.O. 2012. Fact sheets by population – GLOBOCAN 2012: estimated cancer incidence, mortality and prevalence worldwide in 2012; [cited 2014 July 23]. Available from: http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx.
   Google Scholar