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研究生:楊秉憲
研究生(外文):Bing-Xian Yang
論文名稱:以模糊方法分析腦皮質厚度與阿茲罕默症之關聯性
論文名稱(外文):Using fuzzy inference to analyze the associations between cortical thickness and Alzheimer''s disease
指導教授:黃有評黃有評引用關係曾傳蘆曾傳蘆引用關係
口試委員:劉珣瑛張玉山姚立德
口試日期:2013-07-22
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:87
中文關鍵詞:模糊推論系統核磁共振影像腦皮質厚度阿茲罕默症
外文關鍵詞:Fuzzy inferenceMRIcortical thickness
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阿茲罕默症俗稱老人痴呆,是六十五歲以上老年人罹患率最高的失智症,心智功能會逐漸的喪失且無法復原,病因至今仍是個謎,而在這個社會結構老化的年代,老年人口的增加勢必導致患有此疾病的人數增加,除了不易檢查出是否罹患疾病外,由阿茲罕默症所導致的精神症狀也會帶給病患家屬莫大的負擔。因此,若能及早的檢測出是否罹患阿茲罕默症,便能及早預防,延緩退化的速度。近年來有相當多的研究探討大腦皮質厚度異常變化與疾病之間的關係,也證實其之間的關聯性,如阿茲罕默症、自閉症等等。因此,本研究針對大腦皮質與阿茲罕默症之關聯性,使用由哈佛大學所開發的Freesurfer軟體,將正常人與阿茲罕默症病患之腦部核磁共振影像進行分析,畫分出大腦中白質、灰質、基底核及丘腦等部位,並重建出立體之腦模型,最後將皮質厚度資訊截取出來,先進行熱和平滑化篩選厚度特徵,接著計算出皮質厚度同源性之拓樸圖,再將拓樸結果進行模糊分群,最後依皮質厚度拓樸之特徵點建立出模糊推論系統。由實驗結果顯示正常人之關聯性平均為32%,阿茲罕默症患者之關聯性平均為73%,驗證本研究所提出之阿茲罕默症關聯性判斷系統的可行性。

Alzheimer''s disease is one of the dementia forms which has the highest prevalence at the age more than 65. It will cause the decrease of both memory and cognitive ability gradually and we still do not know its causes. In addition, it is also hard to find the disease till the patient shows visible symptoms, and for the families, the burden increases as the disease becomes more severe. However, due to the aging of the society, more and more elderly population are likely to develop Alzheimer''s disease. Hence if we could find some symptoms as early as possible, then we could predict it and slow down the rate of deterioration. In this study, we focus on the correlation between the cortical thickness and Alzheimer''s disease. We use the software named Freesurfer which was developed by Harvard to analyze the brain’s MRI (Magnetic Resonance Imaging). Through it, we can acquire the tissue’s segmentations and reconstruct it into 3D model. Successively, we can obtain the thickness data of the cortex. After that, we use the heat kernel smoothing to filter the thickness features and use the Min-Max diagram to compute the topology of homology, finally we use these results to construct a fuzzy inference system. Results show that the correlation of normal subjects is 32% and the correlation of patients is 73% and it proves the feasibility of proposed system.

摘 要 i
ABSTRACT ii
致謝 iv
目 錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景 1
1.2 研究目的 4
1.3 研究方法 4
1.4 論文架構 5
第二章 相關技術及應用探討 6
2.1 核磁共振影像(Magnetic Resonance Imaging) 6
2.2熱核平滑化(Heat Kernel Smoothing) 8
2.3 Min-Max Diagram 11
2.3.1演算法流程 11
2.3.2模擬實例 12
2.4模糊理論 13
2.4.1 模糊集合 14
2.4.2模糊歸屬函數 14
第三章 系統架構與設計 18
3.1 系統架構 18
3.2 模糊歸屬函數設計 19
3.2.1 模糊歸屬函數設計範例 23
3.3 開發環境 27
3.3.1 硬體規格 27
3.3.2 軟體版本 28
3.3.2.1 Freesurfer 28
3.3.2.2 Matlab 33
3.3.2.3 Microsoft Visual Studio 2010 C# 33
3.3.2.4 Cygwin 34
第四章 實驗結果與分析 36
4.1 實驗架構 36
4.2 Freesurfer重建結果 36
4.3 熱核平滑化(Heat Kernel Smooth)參數選擇 56
4.4 Matlab分析及模糊邏輯系統建立之結果 73
4.5 實驗結果 76
第五章 結論與未來展望 82
5.1 結論 82
5.2 未來展望 83
參考文獻 84


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