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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳中明 | |
dc.contributor.author | Pei-Kai Hung | en |
dc.contributor.author | 洪培凱 | zh_TW |
dc.date.accessioned | 2021-07-11T14:42:36Z | - |
dc.date.available | 2021-11-02 | |
dc.date.copyright | 2016-11-02 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-08-17 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78112 | - |
dc.description.abstract | 動脈粥狀硬化所造成的心血管疾病每年都奪走許多寶貴的性命,已連年佔據台灣十大死因之第二位。電腦斷層掃描影像是主要用來診斷此一疾病之影像工具。為了對這個疾病有更深入的了解,我們透過電腦輔助診斷與全自動的影像分割演算法來重建冠狀動脈結構,並探索血管管腔狹窄所衍伸之問題。
透過優化血管中心線萃取技術並提供血管狹窄程度之整合資訊,本研究致力於建立全自動之電腦輔助診斷於心血管疾病之應用。本研究利用電腦斷層影像發展全自動化之升主動脈分割方法來分割主動脈瓣處的「3顆球」結構,並利用K-mean濾波器進行影像前處理,排除不必要之背景資訊,使本研究中的自適應區域成長演算法得以完整分割冠狀動脈血管。組合所有具血管特徵之像素,並加上血管中心線演算法後,便可對血管管腔中的資訊進行分析。 研究中發現「3顆球」結構之確立有助於降低冠狀動脈起點偵測之難度。而整合灰階值與管狀結構資訊之自適應區域成長演算法能在避免分割影像溢出的情況下得到完整之冠狀動脈網路。藉由血管中心線萃取演算法,我們更得以沿著血管方向分析此一血管路徑上是否發生狹窄、狹窄處之組成成分為何,藉已得到具臨床價值之資訊。 在臨床運用上,本研究之成果將有助於更精準的描述心血管疾病以並提供相關疾病進程之資訊。 | zh_TW |
dc.description.abstract | Atherosclerosis, the leading cause of heart disease, is still ranked as second major cause of death in Taiwan. Multi-slice computed tomography (MSCT) is the conventional strategy for diagnosis. For the assessment of coronary artery disease, an automated computer-aided diagnosis system is essentially needed to clarify both lumen volume and coronary tree.
This research aims to develop automated system, improve the extraction of coronary artery centerline, and provide comprehensive information of stenosis. We collected MSCT images and developed an automated algorithm to extract ascending aorta along with coronary artery from serial computed tomography images. K-means clustering is applied for background exclusion, and the structure of ball-like aortic root is particularly segmented. In self-adjusting region growing scheme, the intensity of each voxel and its neighborhood are both calculated during the establishment of lumen volume. Assembling qualified voxels, the coronary tree is revealed and coronary artery centerline extracted. For further analysis, lumen volume is analyzed after vessel skeletonization is performed. It was demonstrated the delineation of ball-like aortic root would simplify the detection of coronary artery ostium. Integration of neighborhood and vesselness information to the self-adapted region growing scheme was approved to prevent the occurrence of leakage and facilitate the inclusion or exclusion of voxels with similar intensity. With centerline extraction, analysis of vessel profile and quantitation of plaque burden were achieved and diagnostic information acquired. For clinical practice, the automated algorithm and computer-aided tracking system will contribute to consistent and effective assessment for coronary artery disease. | en |
dc.description.provenance | Made available in DSpace on 2021-07-11T14:42:36Z (GMT). No. of bitstreams: 1 ntu-105-D96548023-1.pdf: 4952466 bytes, checksum: 736df308ef93e2934b860b81e948a461 (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 中文摘要 iii ABSTRACT iv 目錄 vi 圖目錄 ix 表目錄 xii Chapter 1 緒論 1 1.1 前言 1 1.1.1 醫療資訊之電子化 1 1.1.2 醫療器材軟體之法規調和 2 1.1.3 電腦輔助診斷之利基 3 1.2 研究動機 4 1.2.1 心血管疾病與肥胖趨勢的全球化 4 1.2.2 動脈粥狀硬化之致病機轉 5 1.2.3 動脈粥狀硬化之診斷方式 6 1.3 研究目的 9 1.3.1 冠狀動脈結構與血管堵塞風險評估 9 1.3.2 冠狀動脈結構偵測之困難 12 1.3.3 本研究之目的與利基 14 1.4 文獻探討 14 1.4.1 血管分割演算法 14 1.4.2 冠狀動脈起點偵測 15 1.4.3 冠狀動脈之血管中心線萃取與血管邊緣分割 17 1.4.4 血管特徵分析 21 1.4.5 關於本研究 23 1.5 論文架構 23 Chapter 2 研究方法與材料 24 2.1 研究材料 24 2.2 研究架構 24 2.3 升主動脈分割 25 2.3.1 升主動脈於首張MSCT影像中的位置 26 2.3.2 以升主動脈為基準之座標轉換 28 2.3.3 由升主動脈偵測冠狀動脈起點 32 2.4 冠狀動脈結構重建 34 2.4.1 管狀結構資訊(Frangi’s filter) 34 2.4.2 海森矩陣之應用(Hessian matrix) 36 2.4.3 整合影像灰階值與管狀結構資訊之區域成長演算法 38 2.5 血管特徵分析 39 2.5.1 血管中心線萃取 39 2.5.2 血管特徵分析 41 Chapter 3 研究結果與討論 44 3.1 簡介 44 3.2 升主動脈分割 44 3.2.1 升主動脈分割結果 44 3.2.2 分割結果說明與討論 47 3.3 冠狀動脈結構重建 47 3.3.1 冠狀動脈重建結果 47 3.3.2 重建結果說明與討論 51 3.4 血管特徵分析 52 3.4.1 血管邊緣分析與比較 52 3.4.2 血管切平面特徵分析結果 56 3.4.3 血管分析結果說明與討論 60 3.5 研究限制 62 3.6 綜合討論與未來展望 63 Chapter 4 結論 64 REFERENCE 65 | |
dc.language.iso | zh-TW | |
dc.title | 使用斷層掃描影像建立全自動的冠狀動脈分割與斑塊定量演算法 | zh_TW |
dc.title | An Automated Algorithm for Coronary Artery Reconstruction and Plaque Burden Assessment in Multi-Slice Computed Tomography | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 王宗道,李文正,蔣以仁,許明暉 | |
dc.subject.keyword | 冠狀動脈分割,主動脈瓣分割,血管中心線萃取,斑塊內容物分析, | zh_TW |
dc.subject.keyword | coronary artery,aortic root,centerline extraction,plaque burden, | en |
dc.relation.page | 71 | |
dc.identifier.doi | 10.6342/NTU201603031 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2016-08-17 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 醫學工程學研究所 | zh_TW |
顯示於系所單位: | 醫學工程學研究所 |
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