• DocumentCode
    2493949
  • Title

    Segmentation of scarred and non-scarred myocardium in LG enhanced CMR images using intensity-based textural analysis

  • Author

    Kotu, Lasya Priya ; Engan, Kjersti ; Eftestøl, Trygve ; Ørn, Stein ; Woie, Leik

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Univ. of Stavanger, Stavanger, Norway
  • fYear
    2011
  • fDate
    Aug. 30 2011-Sept. 3 2011
  • Firstpage
    5698
  • Lastpage
    5701
  • Abstract
    The Late Gadolinium (LG) enhancement in Cardiac Magnetic Resonance (CMR) imaging is used to increase the intensity of scarred area in myocardium for thorough examination. Automatic segmentation of scar is important because scar size is largely responsible in changing the size, shape and functioning of left ventricle and it is a preliminary step required in exploring the information present in scar. We have proposed a new technique to segment scar (infarct region) from non-scarred myocardium using intensity-based texture analysis. Our new technique uses dictionary-based texture features and dc-values to segment scarred and non-scarred myocardium using Maximum Likelihood Estimator (MLE) based Bayes classification. Texture analysis aided with intensity values gives better segmentation of scar from myocardium with high sensitivity and specificity values in comparison to manual segmentation by expert cardiologists.
  • Keywords
    biomedical MRI; cardiology; image segmentation; image texture; maximum likelihood estimation; medical image processing; muscle; Bayes classification; LG enhanced CMR images; cardiac magnetic resonance; dictionary-based texture features; image segmentation; infarct region; intensity-based textural analysis; intensity-based texture analysis; late gadolinium; maximum likelihood estimator; nonscarred myocardium; scarred myocardium; Dictionaries; Image segmentation; Maximum likelihood estimation; Myocardium; Sensitivity; Training; Vectors; Algorithms; Contrast Media; Gadolinium; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging, Cine; Myocardial Stunning; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  • Conference_Location
    Boston, MA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4121-1
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2011.6091379
  • Filename
    6091379