Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/6872
標題: 類神經網路技術於抗核抗體免疫螢光影像分類之應用
ANA Immunofluorescence Image Classification using Neural Network Techniques
作者: 白雯琪
Pai, Wen-Chi
關鍵字: Anti-Nuclear Antibodies;抗核抗體;Indirect Immunofluorescence;Co-occurrence;Fuzzy Texture Spectrum;K-means;Back-propagation Neural Network;間接免疫螢光法;共生矩陣;模糊紋理頻譜;K-means;倒傳遞類神經網路
出版社: 電機工程學系所
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摘要: 
抗核抗體(anti-nuclear antibodies, ANA)的檢查方法為一種間接免疫螢光法(indirect immunofluorescence, IIF),在塗佈目標的細胞玻片上成像,以偵測自體抗體(autoantibody)存在的實驗技術。其判讀方式包括螢光強度指數(intensity index, IF)及型態(pattern)兩大基本要素。然而,國內具有該項專業技術的人員不多,專家眼力、體力受到極大的考驗。明顯的醫療需求,乃需依靠電腦輔助診斷之發展,達到紓緩;本研究以抗核抗體免疫螢光影像為主要的影像分析目標,提出一套適應於抗核抗體醫學影像分類之系統。首先,運用影像像素與其鄰近像素間的灰階值關係,萃取出較適於描述本文實驗影像之特徵。其次,運用k-means降低輸入向量,以透過倒傳遞類神經網路進行網路參數值之訓練。最後,再將原訓練資料丟入先前所訓練的網路參數值中,繼續訓練直到網路收斂為止;由實驗結果中得知,本文所提及之倒傳遞類神經網路概念化的能力,能清楚、明確的描述輸入向量與各類別間的關係。
URI: http://hdl.handle.net/11455/6872
其他識別: U0005-2106201109234900
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