A Novel Quantitative Validation of the Cortical Surface Reconstruction Algorithm Using MRI Phantom: Issues on Local Geometric Accuracy and Cortical Thickness

  • Junki Lee
  • Jong-Min Lee
  • Jae-Hun Kim
  • In Young Kim
  • Alan C. Evans
  • Sun I. Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)


Cortical surface reconstruction is important for functional brain mapping and morphometric analysis of the brain cortex. Several methods have been developed for the faithful reconstruction of surface models which describe the true cortical surface in both geometry and topology. However there has been no explicit method for the quantitative evaluation of the whole-cortical-surface models. In this study, we present a novel phantom-based evaluation method of the cortical surface reconstruction algorithm and quantitatively validated the local morphometric accuracy of CLASP which is one of the well-established reconstruction methods. The evaluation included local geometrical accuracy and performance of cortical thickness measure. The validation study revealed that there were some underestimations of cortical thickness measure using CLASP in the ventral and sulcal areas of the cortex and overestimations in the gyral areas and inferior temporal lobe. This study could present a generic metric for the quantitative evaluation of cortical surface reconstruction algorithm.


Root Mean Square Error Root Mean Square Cortical Thickness Partial Volume Effect Cortical Surface 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Junki Lee
    • 1
  • Jong-Min Lee
    • 1
  • Jae-Hun Kim
    • 1
  • In Young Kim
    • 1
  • Alan C. Evans
    • 2
  • Sun I. Kim
    • 1
  1. 1.Dept. Biomedical EngineeringHanyang UniversitySeoulKorea
  2. 2.McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada

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