• DocumentCode
    2635688
  • Title

    A new method to measure cross sectional area of vessels in MRI image and its application in stenosis detection

  • Author

    Jiang, Jing ; Dong, Ming ; Haacke, E. Mark

  • Author_Institution
    Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
  • fYear
    2004
  • fDate
    15-18 April 2004
  • Firstpage
    1043
  • Abstract
    A new method is introduced in this paper to determine the best means by which to measure the cross sectional area in magnetic resonance images. Images are collected using a three dimensional gradient echo imaging sequence. A dynamic programming based segmentation algorithm is employed to determine the vessel cross section on a slice-by-slice basis. We then estimate the segmentation accuracy as a function of vessel size, sampling matrix, acquisition time and post processing method. We show that there is an optimal value at which the segmentation error is smallest for a fixed set of the aforementioned parameters and that this value scales with the ratio of the vessel diameter to the resolution. Based on the results, it is finally possible to describe how best to collect the data in MRI to be able to determine the vessel´s cross sectional area within a certain accuracy and precision, which is a key missing linking of image processing and image acquisition in MRI field.
  • Keywords
    biomedical MRI; biomedical measurement; blood vessels; diseases; dynamic programming; image segmentation; image sequences; medical image processing; MRI image; acquisition time; blood vessels; cross sectional area measurement; dynamic programming; image acquisition; image processing; magnetic resonance images; post processing method; sampling matrix; segmentation algorithm; segmentation error; slice-by-slice basis; stenosis detection; three dimensional gradient echo imaging sequence; vessel cross sectional area; vessel diameter; Application software; Area measurement; Bifurcation; Biomedical imaging; Blood vessels; Computer science; Dynamic programming; Image segmentation; Magnetic resonance imaging; Radiology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on
  • Print_ISBN
    0-7803-8388-5
  • Type

    conf

  • DOI
    10.1109/ISBI.2004.1398720
  • Filename
    1398720