Segmentation of MRI brain scans into gray matter, white matter and CSF

Tamas Sandor, Hoo Tee Ong, Vladimir I. Valtchinov, Marilyn Albert, Ferenc A. Jolesz

Research output: Contribution to journalConference articlepeer-review


An algorithm is described that can separate gray matter, white matter and CSF in brain scans taken with 3DFFT T1-weighted gradient echo magnetic resonance imaging. Although the algorithm is fully automated, it requires brain contours as input that utilize user-defined features. The inter- and intra-operator errors stemming from the variability of the contour definition and affecting the segmentation were assessed by using coronal brain scans of 19 subjects. The inter-operator errors were (1.61±2.38)% (P=0.01) for gray matter, (0.31±2.06)% (P=0.53) for white matter and (0.28±3.84)% (P=0.76) for cerebrospinal fluid (CSF). the intra-operator error was (0.28±0.55)% (P > 0.04) for gray matter, (0.40±0.37)% (P=0.0002) for white matter and (0.26±1.31)% (P=0.39) for CSF.

Original languageEnglish (US)
Pages (from-to)10-18
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 1 1997
Externally publishedYes
EventMedical Imaging 1997: Image Processing - Newport Beach, CA, United States
Duration: Feb 25 1997Feb 25 1997


  • Brain
  • CSF
  • Gray matter
  • Image processing
  • MRI
  • Segmentation
  • White matter

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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