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研究生: 李彬華
Lee, Pin-Hua
論文名稱: 基於影像自動分割技術對4維全心臟光聲資料進行量化分析用以評估纖維化之方法
An Automatic Segmentation-based Method for Quantified Analysis of 4D Whole-heart Optoacoustic Data to Assess Cardiac Fibrosis
指導教授: 林曉均
Lin, Hsiao-Chun Amy
口試委員: 王廷瑋
Wang, Ting-Wei
宋雁翎
Sung, Yen-Ling
學位類別: 碩士
Master
系所名稱: 原子科學院 - 生醫工程與環境科學系
Department of Biomedical Engineering and Environmental Sciences
論文出版年: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 73
中文關鍵詞: 心臟纖維化光聲斷層掃描逆行心臟灌注醫學影像處理特徵統計分析
外文關鍵詞: Cardiac Fibrosis, Optoacoustic Tomography, Retrograde Heart Perfusion, Medical Image Processing, Feature Statistical Analysis
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  • 心血管疾病是全球最主要的致死原因之一,高死亡率使其成為現今醫學領域亟需解決的重要問題。纖維化作為心血管疾病一個關鍵的病理過程,其顯著影響心臟的舒張與收縮功能,嚴重時還可能會導致心臟衰竭。儘管傳統影像技術在提供心臟結構和功能的基本資訊上發揮了重要作用,但在具備分子對比度情況下要實現完整心臟即時動態影像時仍存在技術瓶頸,限制了纖維化病徵的精確評估。
    在本研究中,通過Langendorff裝置使心臟在體外穩定的環境中,保留了完整的生理功能,並利用光聲斷層掃描技術獲取4維全心臟資料。數據處理部分,首先進行重建參數設定與濾波優化,以確保影像具有較高的訊噪比。接著藉由所提出的演算法對心臟影像進行自動分割,識別邊緣與背景區域。後續在針對特徵值進行強化,以提取用以量化纖維化的生理資訊。
    實驗發現量化心臟尺寸大小和舒張收縮週期中的體積變化差異,可用於分析纖維化對心臟結構與功能的影響。結果顯示,在680 nm雷射波長激發下獲取的數據,具有最明顯的特徵差異。纖維化狀態下的心臟尺寸會大於健康狀態(約8.5%,p = 0.0043),而其在舒張收縮週期中的體積變化差異則小於健康狀態(約4.28%,p = 0.0001),表明了纖維化疾病會對心臟產生負面影響。


    Cardiovascular disease remains one of the foremost causes of mortality globally, presenting a critical challenge in contemporary medicine due to its elevated mortality rates. Fibrosis, as a pivotal pathological process in cardiovascular disease, profoundly impairs both diastolic and systolic cardiac functions. In advanced stages, fibrosis can culminate in heart failure. While conventional imaging modalities provide fundamental insights into cardiac structure and function, they are inherently limited. Achieving real-time dynamic imaging of the entire heart with molecular contrast remains challenging, thereby restricting precise evaluation of fibrosis.
    In this study, an ex vivo model was employed using the Langendorff apparatus to maintain cardiac stability and preserve physiological integrity. Four-dimensional whole-heart data were acquired through optoacoustic tomography, chosen for its ability to provide high-resolution imaging with molecular contrast, enabling detailed visualization of cardiac dynamics that other modalities could not achieve. During the data processing phase, reconstruction parameters and filtering techniques were optimized to maximize the signal-to-noise ratio. Following this, an automated segmentation algorithm was utilized to delineate cardiac boundaries from the background, facilitating accurate image analysis. Subsequently, feature enhancement was conducted to extract key physiological metrics for fibrosis quantification.
    Experimental findings demonstrated that assessing differences in cardiac size and volumetric changes throughout the diastolic and systolic phases provides a robust framework for evaluating the effects of fibrosis on cardiac morphology and function. Specifically, data acquired under 680 nm laser wavelength excitation revealed the most pronounced feature distinctions. The fibrotic heart exhibited a significantly larger size compared to the healthy heart (approximately 8.5%, p = 0.0043) , whereas the volumetric change during the diastolic-systolic cycle was notably reduced (approximately 4.28%, p = 0.0001) , underscoring the deleterious impact of fibrosis on cardiac functionality. These changes imply that fibrosis not only structurally alters the heart but also significantly impairs its ability to effectively contract and relax, which may contribute to the progression towards heart failure and reduced cardiac efficiency in clinical settings.

    摘要 I Abstract II 致謝 (Acknowledgments) III 目錄 (Table of Contents) IV 圖目錄 (List of Figures) VIII 表目錄 (List of Tables) XI 第1章 緒論 (Introduction) 1 1.1. 研究動機 1 1.2. 現有方法與挑戰 1 1.3. 用於纖維化研究的光聲斷層掃描 2 第2章 文獻回顧 (Literature Review) 4 2.1. 心臟纖維化 (Cardiac Fibrosis) 4 2.1.1. 基本概念和發病機制 5 2.1.2. 治療方法和策略 6 2.1.3. 常見之診斷工具 7 2.2. 光聲斷層掃描 (Optoacoustic Tomography) 10 2.2.1. 光聲信號產生與影像形成 11 2.2.2. 光聲技術的優勢 12 2.2.3. 不同的光聲方法 13 2.3. 逆行心臟灌注 (Retrograde Heart Perfusion – Langendorff Technique) 15 2.3.1. Langendorff 技術的原理與裝置建造 16 2.3.2. 可測量之參數與具體應用 18 2.3.3. 現有成果與發展趨勢 19 第3章 研究材料和方法 (Materials and Methods) 21 3.1. 研究材料 (Materials) 21 3.1.1. 小鼠心臟樣本數據 21 3.1.2. 實驗硬體設定 21 3.2. 影像處理和特徵分析之方法 (Processing and Analytical Methods) 23 3.2.1. 重建前參數優化 24 3.2.2. 重建前濾波 26 3.2.3. 重建後濾波 27 3.2.4. 影像中目標區域邊緣偵測和分割 28 3.2.5. 邊緣分割前處理 29 3.2.6. 邊緣分割後處理 29 3.2.7. 心臟體積點數特徵 30 第4章 研究結果 (Results) 31 4.1. 重建前處理 (Preprocessing for Reconstruction) 31 4.1.1. 不同雷射波長下的光聲影像 31 4.1.2. 超音波聲速優化 32 4.1.3. 探測器上元件的分割數量優化 34 4.1.4. 原始信號濾波 39 4.2. 重建後處理 (Postprocessing for Reconstruction) 41 4.2.1. 重建影像濾波 41 4.2.2. 邊緣偵測迭代次數對分割的影響 43 4.2.4. 邊緣偵測閾值對分割的影響 48 4.2.5. 分割前對比度強化 49 4.2.6. 分割後形態學處理 50 4.2.7. 心臟特徵值提取與優化 52 4.3. 特徵值提取 (Feature Extraction) 54 4.3.1. 光聲影像上的處理 54 4.3.2. 分割後三維心臟邊緣影像 55 4.3.3. 特徵值統計 56 4.4. 特徵統計分析 (Feature Statistical Analysis) 57 第5章 討論和結論 (Discussion and Conclusion) 62 5.1. 貢獻與創新點 62 5.2. 挑戰和限制 64 5.3. 未來向與規劃 66 5.4. 本篇研究的結論 68 參考文獻 (References) 70

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