title: Automatic liver segmentation method featuring a novel filter for multiphase multidetector-row helical computed tomography.
abstract: OBJECTIVE
  To introduce an automatic liver segmentation method that includes a novel filter for multiphase multidetector-row helical computed tomography.
  
  
  METHODS
  We acquired 3-phase multidetector-row computed tomographic scans that included unenhanced, arterial, and portal phases. The liver was segmented using our novel adaptive linear prediction filter designed to reduce the difference between filter input and output values in the liver region and to increase these values outside the liver region.
  
  
  RESULTS
  The segmentation algorithm produced a mean dice similarity coefficient (DSC) value of 91.4%.
  
  
  CONCLUSIONS
  The application of our adaptive linear prediction filter was effective in automatically extracting liver regions.
authors.affiliation: Department of Radiology, Shiga University of Medical Science, Otsu City, Shiga, Japan. tomohiro.hirose@nifty.com
authors.forename: Tomohiro
authors.initials: T
authors.lastname: Hirose
authors.forename: Norihisa
authors.initials: N
authors.lastname: Nitta
authors.forename: Masaru
authors.initials: M
authors.lastname: Tsudagawa
authors.forename: Masashi
authors.initials: M
authors.lastname: Takahashi
authors.forename: Kiyoshi
authors.initials: K
authors.lastname: Murata
mesh_terms: D000465:Algorithms; D006801:Humans; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012984:Software; D036542:Tomography, Spiral Computed / Q000379:methods*