A NURBS-Based Technique for the Segmentation of Medical Images

Extracting the human brain from magnetic resonance head scans is difficult because of its highly convoluted and nonuniform geometry. A technique based on Non-Uniform Rational B-Splines (NURBS) and energy minimising deformable models to extract the brain surface accurately from MR head scans is presented. The weighting parameter that comes with the NURBS definition is explored to attract the surface into the regions showing high curvature. The weight at each control point is adjusted automatically according to the curvature properties of the evolving surface. This process facilitates a deformable surface with increased local flexibility that adapts to complex geometrical features of the brain. The results show that the proposed model is capable of capturing the correct brain surface with a higher accuracy than the existing techniques.

[1]  小野 道夫,et al.  Atlas of the Cerebral Sulci , 1990 .

[2]  James M. Ortega,et al.  Model-based boundary estimation of complex objects using hierarchical active surface templates , 1995, Pattern Recognit..

[3]  M. Stella Atkins,et al.  Fully automatic segmentation of the brain in MRI , 1998, IEEE Transactions on Medical Imaging.

[4]  Les A. Piegl,et al.  The NURBS Book , 1995, Monographs in Visual Communication.

[5]  Frithjof Kruggel,et al.  Alignment of magnetic-resonance brain datasets with the stereotactical coordinate system , 1999, Medical Image Anal..

[6]  ISAAC COHEN,et al.  Using deformable surfaces to segment 3-D images and infer differential structures , 1992, CVGIP Image Underst..

[7]  Akshay K. Singh,et al.  Deformable models in medical image analysis , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[8]  Demetri Terzopoulos,et al.  Topology adaptive deformable surfaces for medical image volume segmentation , 1999, IEEE Transactions on Medical Imaging.

[9]  Demetri Terzopoulos,et al.  D NURBS A Physics Based Geometric Design Framework , 1996 .

[10]  James S. Duncan,et al.  Model-based deformable surface finding for medical images , 1996, IEEE Trans. Medical Imaging.

[11]  Christos Davatzikos,et al.  Using a deformable surface model to obtain a shape representation of the cortex , 1996, IEEE Trans. Medical Imaging.

[12]  山浦 晶.  Atlas of the Cerebral Sulci, Michio Ono, Stefan Kubik and Chad D. Abernathey著, Georg Thieme Verlag, Stuttgart, New York 1990(らいぶらりい) , 1992 .

[13]  R. Schafer,et al.  Morphological systems for multidimensional signal processing , 1990, Proc. IEEE.

[14]  Jerry L. Prince,et al.  Reconstruction of the human cerebral cortex from magnetic resonance images , 1999, IEEE Transactions on Medical Imaging.

[15]  L. Piegl.  Modifying the shape of rational B-splines. part2: surfaces , 1989 .

[16]  Hong Qin,et al.  D-NURBS: A Physics-Based Framework for Geometric Design , 1996, IEEE Trans. Vis. Comput. Graph..

[17]  Richard M. Leahy,et al.  Surface-based labeling of cortical anatomy using a deformable atlas , 1997, IEEE Transactions on Medical Imaging.

[18]  G. Bruyn.  Atlas of the Cerebral Sulci, M. Ono, S. Kubik, Chad D. Abernathey (Eds.). Georg Thieme Verlag, Stuttgart, New York (1990), 232, DM 298 , 1990 .

[19]  G. Borgefors.  Distance transformations in arbitrary dimensions , 1984 .

[20]  Max A. Viergever,et al.  Three-dimensional MR brain segmentation , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).