• DocumentCode
    3349438
  • Title

    A fully automated method of associating axial slices with a disc based on labeling of multi-protocol lumbar MRI

  • Author

    Koh, Jaehan ; Chaudhary, Vipin ; Dhillon, Gurmeet

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. at Buffalo (SUNY), Buffalo, NY, USA
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    4341
  • Lastpage
    4344
  • Abstract
    In a clinical setting, sagittal magnetic resonance imaging (MRI) slices along with axial MRI slices are commonly examined to diagnose lower lumbar disorders. Alongside, scan lines by projecting axial slices onto sagittal slices are provided to show the relationship about which axial slice is associated with a particular disc, resulting in better diagnosing disc-related disorders by a radiologist. In this paper, we propose a method to accurately associate an axial MRI with the particular intervertebral disc in a pre-labeled sagittal lumbar region MRI. A statistical distance prior from multi-protocol MR images of 68 patients is used in labeling process to accommodate the variability of the distance among patients of different ages and gender. Experiments with 93 patient data including 465 lumbar discs show that our method can assign the class membership to scan lines with over 92% accuracy.
  • Keywords
    biomedical MRI; medical image processing; neurophysiology; axial MRI slices; axial slices; clinical setting; disc-related disorders; intervertebral disc; lower lumbar disorders; multiprotocol MR images; multiprotocol lumbar MRI; patient data; prelabeled sagittal lumbar region MRI; radiologist; sagittal magnetic resonance imaging slices; sagittal slices; statistical distance prior; Accuracy; Biomedical imaging; Labeling; Magnetic resonance imaging; Pixel; Protocols; Association; Labeling; Localization; Lumbar Discs; MRI; Scan Line;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2010 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-7992-4
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2010.5652393
  • Filename
    5652393