Abstract
The assessment of arterial luminal area, performed by IVUS analysis, is a clinical index used to evaluate the degree of coronary artery disease. In this paper we propose a novel approach to automatically segment the vessel lumen, which combines model-based temporal information extracted from successive frames of the sequence, with spatial classification using the Growcut algorithm. The performance of the method is evaluated by an in vivo experiment on 300 IVUS frames. The automatic and manual segmentation performances in general vessel and stent frames are comparable. The average segmentation error in vessel, stent and bifurcation frames are 0.17±0.08 mm, 0.18±0.07 mm and 0.31±0.12 mm respectively.
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References
Mendizabal-Ruiz, E.G., Biros, G., Kakadiaris, I.A.: An inverse scattering algorithm for the segmentation of the luminal border on intravascular ultrasound data. Med. Image Comput. Comput. Assist. Interv. 12(Pt2), 885–892 (2009)
Unal, G., Bucher, S., Carlier, S., Slabaugh, G., Fang, T., Tanaka, K.: Shape-driven segmentation of the arterial wall in intravascular ultrasound images. IEEE Trans. Inf. Technol. Biomed. 12(3), 335–347 (2008)
Gil, D., Radeva, P., Saludes, J., Mauri, J.: Automatic segmentation of artery wall in coronary ivus images: a probabilistic approach. Comput. Cardiol., 687–690 (2000)
Brusseau, E., Korte, C.D., Mastik, F., Schaar, J., Steen, A.V.D.: Fully automatic contour detection in intravascular ultrasound imaging. IEEE Trans. Med. Imag. 5(27), 108–118 (2004)
Klingensmith, J.D., Shekhar, R., Vince, D.G.: Evaluation of three-dimensional segmentation algorithms for the identification of luminal and medial-adventitial borders in intravascular ultrasound images. IEEE Trans. Med. Imaging 19(10), 996–1011 (2000)
Jianming, H., Xiheng, H.: An approach to automatic segmentation of 3d intravascular ultrasound images. In: Nuclear Science Symposium and Medical Imaging Conference, vol. 3, pp. 1461–1464 (1994)
Sonka, M., Liang, W., Zhang, X., DeJong, S., Collins, S.M., McKay, C.R.: Three-dimensional automated segmentation of coronary wall and plaque from intravascular ultrasound pullback sequences. In: Computers in Cardiology 1995, pp. 637–640 (1995)
Kudo, N., Kanenari, T., Zhang, X., Yamamoto, K.: In vitro study on arterial lumen detection using a correlation technique in ivus, vol. 2, pp. 830–831 (1998)
Vezhnevets, V., Konouchine, V.: Grow-cut - interactive multi-label n-d image segmentation, pp. 150–156 (2005)
Gatta, C., Balocco, S., Ciompi, F., Hemetsberger, R., Leor, O.R., Radeva, P.: Real-time gating of ivus sequences based on motion blur analysis: Method and quantitative validation. Med. Image Comput. Comput. Assist. Interv. 13, 59–67 (2010)
Smith, S.F., Wagner, R.F.: Ultrasound speckle size and lesion signal to noise ratio: verification of theory. Ultrason Imaging 6(2), 174–180 (1984)
Cohen, L., Kimmel, R.: Global minimum for active contour models: A minimal path approach. International Journal of Computer Vision 24, 57–78 (1997)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)
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Balocco, S. et al. (2011). Combining Growcut and Temporal Correlation for IVUS Lumen Segmentation. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_69
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DOI: https://doi.org/10.1007/978-3-642-21257-4_69
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