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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 蕭浩明(Hao-Ming Hsiao) | |
| dc.contributor.author | Ting-Wei Chang | en |
| dc.contributor.author | 張廷瑋 | zh_TW |
| dc.date.accessioned | 2022-11-25T06:33:05Z | - |
| dc.date.copyright | 2021-11-11 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-08-17 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82165 | - |
| dc.description.abstract | 當慢性腎臟病患者的腎功能衰退至不可逆的最後階段，便會成為末期腎臟病而無法維持體內代謝的恆定，臨床上主要的治療方式便是藉由血液透析來維持患者生命。在接受長期且定期的血液透析前，須先於手臂處建立動靜脈瘻管，方能以高血流量來維持體外循環。對於動靜脈瘻管而言最常見的併發症為血管阻塞，若此情形發生，便無法進行有效的血液透析。因此，對於瘻管阻塞情形的長期追蹤與檢測，無疑是血液透析患者的一大課題。目前常見的臨床檢查方式有理學檢查、周邊血管超音波與血管攝影三種，其各有優點但也有其侷限性。隨著透析治療的患者數量不斷增加，追蹤瘻管健康狀況的需求也大增，大量依靠醫事人員經驗和昂貴醫療檢查設備的傳統檢查方法不再適合用於日常追蹤管理。 近年來，應用光學檢測作為非侵入性的疾病檢測方法蔚為大宗，但使用非侵入性光學方法，且針對血液透析動靜脈瘻管的研究卻為數不多。本研究構建一套三維多角度量測系統，硬體搭載近紅外光成像技術，並可由多種角度拍攝手臂影像。擷取之影像可進行後續分析以可視化皮下血管，建立三維血管模型。本研究之演算法框架可分為三大部分，血管影像增強、像素分類骨架提取以及三維立體建模，其中包括多種影像處理技術。經由近紅外攝影裝置擷取之影像，先進行血管影像增強以提升影像對比度並去除背景雜訊。接著進行像素的分類，藉由找出適合的閾值將血管與背景作區分，以此對影像進行二值化並進行血管骨架提取。最後藉由三維建模的方法，透過選擇兩個不同拍攝角度的影像計算血管中心線，擬合後便能建立三維血管模型。此系統可作為動靜脈瘻管狀況的判斷依據，期望能實現動靜脈瘻管阻塞的早期檢測，並達成日常監測的目標。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-25T06:33:05Z (GMT). No. of bitstreams: 1 U0001-1708202121563300.pdf: 5083912 bytes, checksum: 5c05702219a661b221498a3f10621645 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "口試委員審定書-----------------------------------------------------i 誌謝-------------------------------------------------------------ii 摘要------------------------------------------------------------iii Abstract--------------------------------------------------------iv 目錄-------------------------------------------------------------vi 圖目錄---------------------------------------------------------viii 表目錄-----------------------------------------------------------xi 第一章 緒論------------------------------------------------------1 1.1. 前言----------------------------------------------------1 1.2. 動靜脈瘻管簡介-------------------------------------------3 1.2.1. 自體動靜脈瘻管(Arteriovenous Fistula, AVF)---------------3 1.2.2. 人工瘻管(Arteriovenous Graft, AVG)-----------------------5 1.2.3. 血管阻塞-------------------------------------------------5 1.3. 臨床處置方式與標準指引--------------------------------------6 1.3.1. 理學檢查(Physical Examination)---------------------------6 1.3.2. 周邊血管超音波(Peripheral Vascular Ultrasound)------------9 1.3.3. 血管攝影(Angiography)-----------------------------------9 1.4. 研究目的-------------------------------------------------10 1.5. 研究內容與本文架構----------------------------------------11 第二章 文獻探討-------------------------------------------------12 2.1. 靜脈血管定位技術(Vein Pattern Locating Technology)--------12 2.2. 生物血管特徵識別(Vascular Biometrics)---------------------16 第三章 硬體端之多角度影像擷取設備--------------------------------18 3.1. 硬體機構設計---------------------------------------------18 3.2. 近紅外光源-----------------------------------------------24 3.3. 影像擷取設備規格------------------------------------------26 第四章 軟體端之影像後處理與分析建模-------------------------------31 4.1. 演算法框架介紹--------------------------------------------31 4.2. 血管影像增強----------------------------------------------32 4.2.1. CLAHE--------------------------------------------------33 4.2.2. Hessian Based Frangi Vesselness Filter-----------------39 4.2.3. 數學形態學(Mathematical Morphology)---------------------44 4.3. 像素分類骨架提取-------------------------------------------46 4.3.1. 大津演算法(Otsu’s Method)-------------------------------47 4.3.2. Canny邊緣檢測器(Canny Edge Detector)--------------------50 4.3.3. Morphological Skeleton---------------------------------54 4.4. 三維立體建模----------------------------------------------56 4.4.1. 多項式曲線擬合------------------------------------------57 4.4.2. 血管三維重建--------------------------------------------59 第五章 實驗測試與結果討論----------------------------------------62 5.1. 硬體端影像擷取方法-----------------------------------------62 5.2. 軟體端分析後處理流程---------------------------------------63 5.3. 二維血管可視化可行性討論-----------------------------------66 5.4. 三維血管建模可行性討論-------------------------------------69 第六章 結論與未來展望--------------------------------------------71 6.1. 結論------------------------------------------------------71 6.2. 未來展望--------------------------------------------------71 參考文獻---------------------------------------------------------73" | |
| dc.language.iso | zh-TW | |
| dc.subject | 動靜脈瘻管 | zh_TW |
| dc.subject | 血管三維建模 | zh_TW |
| dc.subject | 血液透析 | zh_TW |
| dc.subject | 影像處理 | zh_TW |
| dc.subject | Hemodialysis | en |
| dc.subject | Image Processing | en |
| dc.subject | 3D Reconstruction of Blood Vessels | en |
| dc.subject | Arteriovenous Fistula/ Graft | en |
| dc.title | 近紅外光攝影之血管三維建模系統開發 | zh_TW |
| dc.title | Development of 3D Vascular Modeling System Based on Near-Infrared Photography | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳湘鳳(Hsin-Tsai Liu),楊士進(Chih-Yang Tseng) | |
| dc.subject.keyword | 動靜脈瘻管,血液透析,影像處理,血管三維建模, | zh_TW |
| dc.subject.keyword | Arteriovenous Fistula/ Graft,Hemodialysis,Image Processing,3D Reconstruction of Blood Vessels, | en |
| dc.relation.page | 83 | |
| dc.identifier.doi | 10.6342/NTU202102446 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2021-08-18 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| dc.date.embargo-lift | 2026-08-18 | - |
| Appears in Collections: | 機械工程學系 | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| U0001-1708202121563300.pdf Restricted Access | 4.96 MB | Adobe PDF | View/Open |
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