• DocumentCode
    1253460
  • Title

    Automatic detection of the mid-sagittal plane in 3-D brain images

  • Author

    Ardekani, Babak A. ; Kershaw, Jeff ; Braun, Michael ; Kanuo, I.

  • Author_Institution
    Dept. of Radiol. & Nucl. Med., Res. Inst. for Brain & Blood Vessels, Akita, Japan
  • Volume
    16
  • Issue
    6
  • fYear
    1997
  • Firstpage
    947
  • Lastpage
    952
  • Abstract
    This article presents a detailed description of an algorithm for the automatic detection of the mid-sagittal plane in three-dimensional (3-D) brain images. The algorithm seeks the plane with respect to which the image exhibits maximum symmetry. For a given plane, symmetry is measured by the cross-correlation between the image sections lying on either side. The search for the plane of maximum symmetry is performed by using a multiresolution approach which substantially decreases computational time. The choice of the starting plane was found to be an important issue in optimization. A method for selecting the initial plane is presented. The algorithm has been tested on brain images from various imaging modalities in both humans and animals. Results were evaluated by visual inspection by neuroradiologists and were judged to be consistently correct.
  • Keywords
    brain; image registration; medical image processing; optimisation; pattern recognition; 3-D brain images; animals; automatic detection algorithm; computational time decrease; humans; image sections cross-correlation; initial plane; maximum symmetry; mid-sagittal plane; neuroradiologists; optimization; starting plane; Biomedical imaging; Blood vessels; Brain; Image edge detection; Image registration; Nuclear medicine; Positron emission tomography; Radiology; Spatial resolution; Testing; Algorithms; Brain; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Tomography, Emission-Computed;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.650892
  • Filename
    650892