SONG Yong-Rui, SHENG Mao, LI Cheng, SUI Dong-li, WANG Zhen-huan. The planar regression analysis and building of the stereotatic data set of sulcus of the insula of human brain[J]. Journal of Bengbu Medical University, 2014, 38(1): 14-18.
    Citation: SONG Yong-Rui, SHENG Mao, LI Cheng, SUI Dong-li, WANG Zhen-huan. The planar regression analysis and building of the stereotatic data set of sulcus of the insula of human brain[J]. Journal of Bengbu Medical University, 2014, 38(1): 14-18.

    The planar regression analysis and building of the stereotatic data set of sulcus of the insula of human brain

    • Objective:To build the stereotactic data set and the planar regression equation of sulcus of the insula,based on the Descartes coordinate system which was set on the line between the anterior commissure and the posterior commissure.Methods:After the strict image registration,the coordinate system of the software coincides with the Descartes coordinate system based on AC-PC line were made.Then the coordinates of the central insular sulcus,the anterior periisular sulcus and the inferior periisular sulcus were recorded,the X-value and Y-value of the sample point was recorded directly from the software,the Z-value is the number of distance from recorded plane to the AC-PC plane.The stereotactic data set of the insular sulcus were constituted by all the coordinate values of sample points of insula,then the regression equations were fetched which were analysed by the SPSS13.0 software.Results:The threedimensional stereotactic data set and the regression equation of the insular sulcus were constructed successfully.Conclusions:The construction of the insular stereotactic data set could provide anatomic basis for the application of stereotactic and functional neurosurgery,three-dimensional radiotherapy,and simultaneously uncovered the significant rules of the development of basilar parts of the human brain.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return