1Institute of Statistical Science, Academia Sinica, No. 128, Sec. 2, Academia Road, Taipei 115, Taiwan.
2Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 106, Taiwan.
*Corresponding author: E-mail: chchuang@stat.sinica.edu.tw
** E-mail: pcheng@stat.sinica.edu.tw
*** E-mail: mliou@stat.sinica.edu.tw
**** E-mail: cyliou@csie.ntu.edu.tw;
***** E-mail: r90047@ms.csie.ntu.edu.tw
This paper presents the application of a self-organizing map (SOM) model for the reconstruction of cerebral cortex from MRI images. The cerebral cortex is an important tissue for many brain science or medicine related researches. Since it is difficult to extract the highly folded and buried cortical surface, we apply the SOM model to deform the easily extracted white matter surface on a layered distance map to obtain the cortical surface. The layered distance map is calculated according to the extracted white matter surface and segmented gray matter. The proposed method can reconstruct the proper cortical surface and thus make the measurement of cortical thickness easy. The simulations on T1-weighted MRI images show that the proposed algorithm is robust to reconstruct the cerebral cortex.
self-organizing map, surface reconstruction, cerebral cortex, cortical thickness, layered distance map
