title: Application of a semiautomated contour segmentation tool to identify the intervertebral nucleus pulposus in MR images.
abstract: OBJECTIVE
  Accurate identification of the NP in MR images is crucial to properly and objectively assess the intervertebral disk. Therefore, computerized segmentation of the NP in T2WI is necessary to produce repeatable and accurate results with minimal user input.
  
  
  METHODS
  A semiautomated CS method was developed to identify the NP in T2WI on the basis of intensity differences compared with the AF. The method was validated by segmenting computer-generated images with a known ROI. The method was tested by using 63 MR images of rabbit lumbar disks, which were segmented to detect disk degeneration. An ICC was used to assess the repeatability of this method compared with manual segmentation.
  
  
  RESULTS
  The error in the detected area of the rabbit NP by using CS was -3.49% ± 4.4% (mean ± SD) compared with 22.36% ± 5.55% by using manual segmentation. Moreover, the method was capable of detecting disk degeneration in a known rabbit puncture model of disk degeneration. Finally, this method had an ICC of 0.97 and 0.99 in regard to segmenting the area and calculating the MR imaging index of the NP, deeming it highly repeatable.
  
  
  CONCLUSIONS
  The CS method is a semiautomated computer method able to segment the NP of the rabbit disk and detect disk degeneration. In addition, it could assist in clinical detection, assessment, and monitoring of early degeneration in human disks.
authors.affiliation: Department of Orthopaedic Surgery, Ferguson Laboratory for Orthopaedic Research, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15213, USA.
authors.forename: B P
authors.initials: BP
authors.lastname: Bechara
authors.forename: S K
authors.initials: SK
authors.lastname: Leckie
authors.forename: B W
authors.initials: BW
authors.lastname: Bowman
authors.forename: C E
authors.initials: CE
authors.lastname: Davies
authors.forename: B I
authors.initials: BI
authors.lastname: Woods
authors.forename: E
authors.initials: E
authors.lastname: Kanal
authors.forename: G A
authors.initials: GA
authors.lastname: Sowa
authors.forename: J D
authors.initials: JD
authors.lastname: Kang
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007403:Intervertebral Disc / Q000033:anatomy & histology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011817:Rabbits; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity