Intensity Gradient Self-organizing Map for Cerebral Cortex Reconstruction

  • Authors:

  • Cheng-Hung Chuang;Jiun-Wei Liou;Philip E. Cheng;Michelle Liou;Cheng-Yuan Liou

  • Affiliations:

  • Dept. of Computer Science and Information Eng., Asia University, Taichung, Taiwan;Institute of Statistical Science, Academia Sinica, Taipei, Taiwan and Dept. of Computer Science and Information Eng., National Taiwan Univ., Taipei, Taiwan;Institute of Statistical Science, Academia Sinica, Taipei, Taiwan;Institute of Statistical Science, Academia Sinica, Taipei, Taiwan;Dept. of Computer Science and Information Eng., National Taiwan Univ., Taipei, Taiwan

  • Venue:
  • Neural Information Processing
  • Year:
  • 2007

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Abstract

This paper presents an application of a self-organizing map (SOM) model based on the image intensity gradient for the reconstruction of cerebral cortex from MR images. The cerebral cortex reconstruction is important for many brain science or medicine related researches. However, it is difficult to extract deep cortical folds. In our method, we apply the SOM model based on the image intensity gradient to deform the easily extracted white matter surface and extract the cortical surface. The intensity gradient vectors are calculated according to the intensities of image data. Thus the proper cortical surface can be extracted from the image information itself but not artificial features. The simulations on T1-weighted MR images show that the proposed method is robust to reconstruct the cerebral cortex.