• DocumentCode
    3438381
  • Title

    Vascular segmentation in magnetic resonance angiography: A modified region growing approach

  • Author

    Almi´ani, M.M. ; Barkana, Buket D.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Bridgeport, Bridgeport, CT, USA
  • fYear
    2012
  • fDate
    1-1 Dec. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A modified region growing algorithm is proposed to extract cerebral vessels using a magnetic resonance angiography (MRA) database. To improve the performance of the image segmentation method, as a pre-processing step, image enhancement methods are applied by the gamma correction technique and spatial operations. This step improves the detection of gray-level discontinuities in MRA images. The traditional region growing method is modified by extending the neighborhood as 24 pixels and by defining a filling protocol to label vascular structure. The performance of the proposed algorithm is compared with that of the traditional region growing method and four other segmentation methods. The minimum and maximum errors of the modified region growing algorithm is calculated as zero and 1.11%, respectively while the traditional region growing method has 0.2% and 7.81%.
  • Keywords
    biomedical MRI; blood vessels; brain; feature extraction; image enhancement; image segmentation; medical image processing; MRA; cerebral vessel extraction; gamma correction; gray-level discontinuities; image enhancement method; magnetic resonance angiography; magnetic resonance angiography database; modified region growing algorithm; spatial operations; vascular segmentation; Angiography; Blood vessels; Educational institutions; Image segmentation; Magnetic resonance; Magnetic resonance angiography (MRA); block-by-block operation; image segmentation; point detection; region growing method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing in Medicine and Biology Symposium (SPMB), 2012 IEEE
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-5665-7
  • Type

    conf

  • DOI
    10.1109/SPMB.2012.6469450
  • Filename
    6469450