• DocumentCode
    1396718
  • Title

    Fully automatic identification of AC and PC landmarks on brain MRI using scene analysis

  • Author

    Vérard, Laurent ; Allain, Pascal ; Travère, Jean Marcel ; Baron, Jean Claude ; Bloyet, Daniel

  • Author_Institution
    CNRS, Caen, France
  • Volume
    16
  • Issue
    5
  • fYear
    1997
  • Firstpage
    610
  • Lastpage
    616
  • Abstract
    Describes a method for identification of brain structures from MRI data sets. The bulk of the paper concerns an automatic system for finding the anterior and posterior commissures [(AC) and (PC)] in the midsagittal plane. These landmarks are key for the definition of the Talairach space, commonly used in stereotactic neurosurgery, in the definition of common coordinate systems for the pooling of functional positron emission tomography (PET) images and for neuroanatomy studies. The process works according to a step-by-step procedure: it first analyzes the skull limits. A grey-level histogram is then calculated and allows an automated selection of thresholds. Then, the interhemispheric plane is detected. Following an advanced scene analysis in the midsagittal plane for anatomical structures, the AC and the PC are identified. Experimentally, with a set of 200 patients, the process never failed. Its performances and limits are comparable to that of neuroanatomy experts. Those results are due to a high degree of robustness at each step of the program.
  • Keywords
    biomedical NMR; brain; feature extraction; medical image processing; AC landmarks; PC landmarks; Talairach space definition; anatomical structures; brain MRI; common coordinate systems; fully automatic identification; functional positron emission tomography images; grey-level histogram; interhemispheric plane; magnetic resonance imaging; medical diagnostic imaging; midsagittal plane; neuroanatomy studies; scene analysis; Anatomical structure; Brain; Computed tomography; Histograms; Image analysis; Magnetic resonance imaging; Neurosurgery; Positron emission tomography; Robustness; Skull; Algorithms; Automatic Data Processing; Brain; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Neuroanatomy; Observer Variation; Pattern Recognition, Automated; Reproducibility of Results; Skull; Stereotaxic Techniques; Superior Colliculi; Tomography, Emission-Computed;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.640751
  • Filename
    640751