Cerebral cortex, classified as gray matter, is the superficial layer of the cerebrum. In recent years, many studies have shown the abnormality of cortical thickness is possibly correlated to the disease or disorder in central nervous system, such as Alzheimer¡¦s disease and lissencephaly. Therefore, this purpose of this work is to implement the measurement of the cortical thickness.
In general, two approaches, surface-based and voxel-based methods, have been proposed to measure the cortical thickness. In this thesis, a procedure of the voxel-based method using Laplace¡¦s equation was developed on the basis of a 2008 publication reported by Chloe Hutton et al to obtain voxel-based cortical thickness (VBCT) map. The result of our home-made program was further compared with those calculated by Hutton¡¦s program, whic h was generously provided by the author. The difference between two implementations was consisted of four main parts. First of all, different strategies of the tissue classification were used to define boundary condition of Laplace¡¦s equation. When grey matter, white matter, and cerebrospinal fluid were classified by maximizing the tissue probability, Hutton¡¦s program tends to search more voxels of cerebrospinal fluid in sulci by skeletonizing the non-parenchyma area. Second, the algorithm of layer growing also differs. The single layer obtained by the 26-neighborhood algorithm in our program would be obviously thicker than that provided by Hutton¡¦s program using 6-neighborhood. Third, compared with a fixed step size (usually 0.5 mm) porposed in the main reference to track cortical streamline, we designed a variable step size, reducing the underestimation of cortical thickness. The last but not the least, the connecting points of the cortical streamline usually are not grid points, thus requiring interpolation to estimate the stepping gradient. We adapted the linear interpolation for better accuracy when Hutton et al searched for the closest grid point for replacement to achieve faster computation.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0214112-143029 |
| Date | 14 February 2012 |
| Creators | Chen, Wen-Fu |
| Contributors | Pin-Jen Yang, MING-TING WU, Tzu-Chao Chuang, Teng-Yi Huang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0214112-143029 |
| Rights | user_define, Copyright information available at source archive |
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