title: Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI.
abstract: OBJECTIVE
  To automatically segment multiple sclerosis (MS) lesions into three subtypes (i.e., enhancing lesions, T1 "black holes", T2 hyperintense lesions).
  
  
  METHODS
  Proton density-, T2- and contrast-enhanced T1-weighted brain images of 12 MR scans were pre-processed through intracranial cavity (IC) extraction, inhomogeneity correction and intensity normalization. Intensity-based statistical k-nearest neighbor (k-NN) classification was combined with template-driven segmentation and partial volume artifact correction (TDS+) for segmentation of MS lesions subtypes and brain tissue compartments. Operator-supervised tissue sampling and parameter calibration were performed on 2 randomly selected scans and were applied automatically to the remaining 10 scans. Results from this three-channel TDS+ (3ch-TDS+) were compared to those from a previously validated two-channel TDS+ (2ch-TDS+) method. The results of both the 3ch-TDS+ and 2ch-TDS+ were also compared to manual segmentation performed by experts.
  
  
  RESULTS
  Intra-class correlation coefficients (ICC) of 3ch-TDS+ for all three subtypes of lesions were higher (ICC between 0.95 and 0.96) than that of 2ch-TDS+ for T2 lesions (ICC = 0.82). The 3ch-TDS+ also identified the three lesion subtypes with high specificity (98.7-99.9%) and accuracy (98.5-99.9%). Sensitivity of 3ch-TDS+ for T2 lesions was 16% higher than with 2ch-TDS+. Enhancing lesions were segmented with the best sensitivity (81.9%). "Black holes" were segmented with the least sensitivity (62.3%).
  
  
  CONCLUSIONS
  3ch-TDS+ is a promising method for automated segmentation of MS lesion subtypes.
authors.affiliation: Center for Neurological Imaging, Departments of Radiology and Neurology, Brigham and Women's Hospital, Harvard Medical School, 221 Longwood Avenue RF394A, Boston, MA 02115, USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Wu
authors.forename: Simon K
authors.initials: SK
authors.lastname: Warfield
authors.forename: I Leng
authors.initials: IL
authors.lastname: Tan
authors.forename: William M
authors.initials: WM
authors.lastname: Wells
authors.forename: Dominik S
authors.initials: DS
authors.lastname: Meier
authors.forename: Ronald A
authors.initials: RA
authors.lastname: van Schijndel
authors.forename: Frederik
authors.initials: F
authors.lastname: Barkhof
authors.forename: Charles R G
authors.initials: CR
authors.lastname: Guttmann
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000473:pathology; D002138:Calibration; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000473:pathology*; D015203:Reproducibility of Results