• DocumentCode
    1401612
  • Title

    Precise segmentation of the lateral ventricles and caudate nucleus in MR brain images using anatomically driven histograms

  • Author

    Worth, Andrew J. ; Makris, Nikos ; Patti, Mark R. ; Goodman, Julie M. ; Hoge, Elizabeth A. ; Caviness, Verne S., Jr. ; Kennedy, David N.

  • Author_Institution
    Center for Morphometric Anal., Massachusetts Gen. Hosp., Boston, MA, USA
  • Volume
    17
  • Issue
    2
  • fYear
    1998
  • fDate
    4/1/1998 12:00:00 AM
  • Firstpage
    303
  • Lastpage
    310
  • Abstract
    This paper demonstrates a time-saving, automated method that helps to segment the lateral ventricles and caudate nucleus in T1-weighted coronal magnetic resonance (MR) brain images of normal control subjects. The method involves choosing intensity thresholds by using anatomical information and by locating peaks in histograms. To validate the method, the lateral ventricles and caudate nucleus were segmented in three brain scans by four experts, first using an established method involving isointensity contours and manual editing, and second using automatically generated intensity thresholds as an aid to the established method. The results demonstrate both time savings and increased reliability.
  • Keywords
    biomedical NMR; brain; image segmentation; medical image processing; MR brain images; MRI; T1-weighted coronal magnetic resonance brain images; anatomically driven histograms; automatically generated intensity thresholds; caudate nucleus; lateral ventricles; medical diagnostic imaging; neuromorphometry; normal control subjects; precise segmentation; time-saving automated method; Automatic control; Automation; Brain; Histograms; Hospitals; Image segmentation; Magnetic resonance; Magnetic resonance imaging; Neuroscience; Noise robustness; Adult; Algorithms; Caudate Nucleus; Cerebral Ventricles; Child; Corpus Callosum; Female; Humans; Image Enhancement; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Reproducibility of Results; Time Factors;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.700743
  • Filename
    700743