Computerized Medical Imaging and Graphics
Volume 36, Issue 1 , Pages 25-37 , January 2012

Left ventricular myocardium segmentation on arterial phase of multi-detector row computed tomography

  • I-Chen Tsai

      Affiliations

    • Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan
    • Institute of Clinical Medicine, National Yang Ming University, Taiwan
  • ,
  • Yu-Len Huang

      Affiliations

    • Department of Computer Science, Tunghai University, Taichung 407, Taiwan
    • Corresponding Author InformationCorresponding author. Tel.: +886 4 23590121x33800; fax: +886 4 23591567.
  • ,
  • Kai-Hua Kuo

      Affiliations

    • Department of Computer Science, Tunghai University, Taichung 407, Taiwan

Received 25 November 2009 ,Revised 23 July 2010 ,Accepted 18 March 2011.

References 

  1. Dewey M, Muller M, Eddicks S, Schnapauff D, Teige F, Rutsch W, et al. Evaluation of global and regional left ventricular function with 16-slice computed tomography, biplane cineventriculography, and two-dimensional transthoracic echocardiography: comparison with magnetic resonance imaging. J Am Coll Cardiol. 2006;48:2034–2044
  2. Tsai IC, Lee WL, Tsao CR, Chang Y, Chen MC, Lee T, et al. Comprehensive evaluation of ischemic heart disease using MDCT. AJR Am J Roentgenol. 2008;191:64–72
  3. Tsai IC, Huang YL, Liao WC, Kuo KH, Chen MC. Left ventricular myocardial volumes measured during arterial and delayed phases of multidetector row computed tomography: a study on intra- and interobserver variability. Int J Cardiovasc Imaging (formerly Cardiac Imaging). 2009;25:55–63
  4. Boehm T, Alkadhi H, Roffi M, Willmann JK, Desbiolles LM, Marincek B, et al. Time-effectiveness, observer-dependence, and accuracy of measurements of left ventricular ejection fraction using 4-channel MDCT. Rofo. 2004;176:529–537
  5. Okuyama T, Ehara S, Shirai N, Sugioka K, Ogawa K, Oe H, et al. Usefulness of three-dimensional automated quantification of left ventricular mass, volume, and function by 64-slice computed tomography. J Cardiol. 2008;52:276–284
  6. Mahnken AH, Katoh M, Bruners P, Spuentrup E, Wildberger JE, Gunther RW, et al. Acute myocardial infarction: assessment of left ventricular function with 16-detector row spiral CT versus MR imaging – study in pigs. Radiology. 2005;236:112–117
  7. Mahnken AH, Koos R, Katoh M, Wildberger JE, Spuentrup E, Buecker A, et al. Assessment of myocardial viability in reperfused acute myocardial infarction using 16-slice computed tomography in comparison to magnetic resonance imaging. J Am Coll Cardiol. 2005;45:2042–2047
  8. Sato A, Hiroe M, Nozato T, Hikita H, Ito Y, Ohigashi H, et al. Early validation study of 64-slice multidetector computed tomography for the assessment of myocardial viability and the prediction of left ventricular remodelling after acute myocardial infarction. Eur Heart J. 2008;29:490–498
  9. Lardo AC, Cordeiro MA, Silva C, Amado LC, George RT, Saliaris AP, et al. Contrast-enhanced multidetector computed tomography viability imaging after myocardial infarction: characterization of myocyte death, microvascular obstruction, and chronic scar. Circulation. 2006;113:394–404
  10. Koyama Y, Matsuoka H, Mochizuki T, Higashino H, Kawakami H, Nakata S, et al. Assessment of reperfused acute myocardial infarction with two-phase contrast-enhanced helical CT: prediction of left ventricular function and wall thickness. Radiology. 2005;235:804–811
  11. George RT, Jerosch-Herold M, Silva C, Kitagawa K, Bluemke DA, Lima JA, et al. Quantification of myocardial perfusion using dynamic 64-detector computed tomography. Invest Radiol. 2007;42:815–822
  12. Lee HY, Codella N, Cham M, Prince M, Weinsaft J, Wang Y. Left ventricle segmentation using graph searching on intensity and gradient and a priori knowledge (lvGIGA) for short-axis cardiac magnetic resonance imaging. J Magn Reson Imaging. 2008;28:1393–1401
  13. Lynch M, Ghita O, Whelan PF. Left-ventricle myocardium segmentation using a coupled level-set with a priori knowledge. Comput Med Imaging Graph. 2006;30:255–262
  14. Lynch M, Ghita O, Whelan PF. Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model. IEEE Trans Med Imaging. 2008;27:195–203
  15. Codella NC, Weinsaft JW, Cham MD, Janik M, Prince MR, Wang Y. Left ventricle: automated segmentation by using myocardial effusion threshold reduction and intravoxel computation at MR imaging. Radiology. 2008;248:1004–1012
  16. Jolly MP. Automatic segmentation of the left ventricle in cardiac MR and CT images. Int J Comput Vision. 2006;70:151–163
  17. Adams R, Bischof L. Seeded Region Growing. IEEE Trans Pattern Anal Mach Intell. 1994;16:641–647
  18. Dagher I, El Tom K. WaterBalloons: a hybrid watershed Balloon Snake segmentation. Image Vision Comput. 2008;26:905–912
  19. Kass M, Witkin A. Terzopoulos D: snakes – active contour models. Int J Comput Vision. 1987;1:321–331
  20. Vincent L, Soille P. Watersheds in digital spaces – an efficient algorithm based on immersion simulations. IEEE Trans Pattern Anal Mach Intell. 1991;13:583–598
  21. Lorenzo-Valdes M, Sanchez-Ortiz GI, Elkington AG, Mohiaddin RH, Rueckert D. Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. Med Image Anal. 2004;8:255–265
  22. Lotjonen J, Kivisto S, Koikkalainen J, Smutek D, Lauerma K. Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images. Med Image Anal. 2004;8:371–386
  23. Hamarneh G, Li X. Watershed segmentation using prior shape and appearance knowledge. Image Vision Comput. 2009;27:59–68
  24. Gonzalez RC, Woods RE. Digital image processing. 3rd ed.. New Jersey: Pearson Prentice Hall; 2010;
  25. Huang YL, Jiang YR, Chen DR, Moon WK. Level set contouring for breast tumor in sonography. J Digit Imaging. 2007;20:238–247
  26. Malladi R, Sethian JA, Vemuri BC. Shape modeling with front propagation – a level set approach. IEEE Trans Pattern Anal Mach Intell. 1995;17:158–175
  27. Perona P, Malik J. Scale-space and edge-detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell. 1990;12:629–639
  28. Barber CB, Dobkin DP, Huhdanpaa HT. The Quickhull algorithm for convex hulls. ACM Trans Math Software. 1996;22:469–483
  29. Ibanez L, Schroeder W, Ng L, Cate J. The ITK guide – updated for ITK version 2.4, 2nd ed.; available online at http://www.itk.org/ItkSoftwareGuide.pdf, Nov. 2005.
  30. Lefohn AE, Cates JE, Whitaker RT. Interactive GPU-based level sets for 3D segmentation. Med Image Comput Comput Assist Interv – Miccai. 2003;2878:564–572
  31. Anbeek P, Vincken KL, van Osch MJ, Bisschops RH, van der Grond J. Probabilistic segmentation of white matter lesions in MR imaging. Neuroimage. 2004;21:1037–1044

PII: S0895-6111(11)00046-2

doi: 10.1016/j.compmedimag.2011.03.003

Computerized Medical Imaging and Graphics
Volume 36, Issue 1 , Pages 25-37 , January 2012