| 研究生: |
蘇育正 Su, Yu-Cheng |
|---|---|
| 論文名稱: |
運用特徵對應與區塊比對於參數化球上的腦皮層對位 Cortex Mapping on Parameterized Sphere Using Feature Correspondence and Block Matching |
| 指導教授: |
孫永年
Sun, Yung-Nien |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 資訊工程學系 Department of Computer Science and Information Engineering |
| 論文出版年: | 2006 |
| 畢業學年度: | 94 |
| 語文別: | 中文 |
| 論文頁數: | 55 |
| 中文關鍵詞: | 腦皮層 、對位 、特徵 、調準 、攤平 、區塊比對 |
| 外文關鍵詞: | cortex mapping, mean curvature, feature, align, block matching |
| 相關次數: | 點閱:87 下載:2 |
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在神經科學研究中,瞭解人類腦皮層結構和腦功能之間的關係是腦皮層對位的主要目的。由於每個人大腦發展程度不一致,所以不同的大腦之間在解剖結構與形態上可能存在著極大的差異性,不容易直接達成腦皮層之間的對位。於是我們將不同的腦皮層對應到同一標準空間,在此標準空間中求得不同腦皮層之間的對應關係。
藉由核磁共振造影(MRI)所取得的腦部影像,可以經由前處理去除頭骨、頭皮並分割出白質、灰質、腦脊髓液的部分,接著以灰白質為主體重構出三維腦皮層網格模型。但由於產生的模型必定會夾帶許多雜訊,使得主要特徵部分並不明顯,經過簡化、平滑化之後,可以讓主要的腦溝、腦迴較為清楚易見。之後由使用者半自動地指定部分對應的腦溝特徵,在各別攤平模型之後,根據已指定的對應特徵,將攤平後的模型做初步特徵的調準,再將模型對應至球面空間上,在擁有已對應特徵的良好初始情況下,進行球面上的區塊比對,以求取腦皮層模型之間的對應關係。
根據所得的對應關係,便可分析和比較不同腦皮層結構上的差異,如不同年齡層或不同性別,亦可依據對應關係,將腦皮層做形變,以建立多個不同腦皮層的平均模型。此外,我們利用形變前後的特徵區域的重疊程度和腦皮層模型曲率變化,以驗證對應正確與否。
In neuroscience research, the main goal in human cortex mapping is to understand the relationship between the structure of cortex and brain function. Due to the inconsistency in brain development, there may exist tremendous differences in anatomy and morphology from brain to brain. Therefore, it is not easy to register cortices directly. We map different cortices to the same standard space in which the correspondence is obtained.
The MRI volume data is pre-processed to remove the skull and the scalp. After segmentation, we will get three parts – WM (white matter), GM (gray matter) and CSF (cerebral spinal fluid). By defining WM and GM as the principal part of the brain, the mesh model of the cortex can be constructed. However, a lot of noise will go along with the construction and make the main features unapparent. To make the main sulci and gyri prominent, surface reduction and inflation is necessary. The user may assign feature regions and correspondences on the cortex model semi-automatically. In other words, features can be aligned according to the assignment and correspondence on the flattened images. Then, we map the flattened model to the standard space (sphere). Now we have the initially-aligned condition, and the following step is to perform block matching on the sphere to get the exact correspondence between cortex models.
From the correspondence, we can analyze and compare the structural difference of cortices, ex. the difference between age groups, the difference between males and females. We can also morph the cortex to construct the average shape of several cortices. To verify our methods, the degree of overlapping of feature regions and the curvature variations are evaluated.
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