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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蕭浩明 | zh_TW |
dc.contributor.advisor | Hao-Ming Hsiao | en |
dc.contributor.author | 郭縉 | zh_TW |
dc.contributor.author | KUO CHIN | en |
dc.date.accessioned | 2023-03-19T22:27:42Z | - |
dc.date.available | 2023-12-25 | - |
dc.date.copyright | 2022-09-06 | - |
dc.date.issued | 2022 | - |
dc.date.submitted | 2002-01-01 | - |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84827 | - |
dc.description.abstract | 腎臟疾病在台灣盛行許久,其嚴重程度在世界上的排名更是名列前茅。而在腎臟病嚴重影響到病患的生理機能時,洗腎便是無可避免的。台灣洗腎多數採用血液透析的方式,血液透析透通常需要在手臂放置瘻管增強血液循環中的血流以加速洗腎的效率,但瘻管伴隨的問題是血管的阻塞,故瘻管的健康程度對洗腎病患來說相當的重要。檢查血管阻塞的方法有許多種,但這些方法不外乎都需要專業人員的操作及判讀,甚至是進行侵入式手術。在台灣眾多的洗腎病患下,光是為了檢測瘻管的健康程度便會造成醫療上面的巨大負擔。近年影像處理相關的應用越來越廣,其中在醫療方面的研究更是族繁不及備載。影像的好處在於可以透過非侵入式的方式進行,並且操作簡易。 本研究與台大新竹分院的吳志成主任合作,從台大新竹分院中收取六位的洗腎患者進行研究。此六位患者會在血管通暢和阻塞時各進行影像的拍攝並透過影像處理的方式進行血管健康程度的分析。 本研究拆成兩部分,第一個部分將探討遠距光體積變化描紀圖(rPPG)在手臂上的可行性。此部分對現有的文獻進行討論,以及透過血管擷取的改良方法進行比較,而改良的方法對手臂的rPPG方法可以看出具有發展性。第二個部分會藉由尤拉影像放大的方式,將手臂的細微跳動放大,並透過光流法抓取像素的位移量,透過影片時間內的位移總和轉為色彩圖以直觀的方式觀察血管阻塞時和健康時的差別;另外記錄每一幀下手臂的平均跳動,觀察長時間跳動的變化,本研究透過訊噪比(SNR)以及曲線擬合得到的方均差進行量化,並在訊噪比的量化能從現有的病患資料得到一個初步的分界標準,對未來相關研究開闢一個新的研究方向。 | zh_TW |
dc.description.abstract | Kidney disease has been prevalent for many years in Taiwan. The epidemic rate is even at the front tier in the world. When kidney disease starts to erode the kidney and cause irreversible damage, having dialysis is inevitable. In Taiwan, the most common way of dialysis is Hemodialysis. Hemodialysis will create outer blood circulation to fasten the speed of dialysis. But by doing so, vascular occlusion will occur easily. There’re lots of ways to examine the severity of occlusion, but most of them require professionals to operate. The examination itself costs lots of medical resources. Recently, image processing has been applied to different medical uses. Image processing can create a non-invasive and professional-less way to monitor our health conditions. In the research, we cooperate with doctor Wu in National Taiwan Hospital Hsin-Chu Branch. Collecting 6 patients having dialysis, we would take their forearms’ video when there’s occlusion occured and occlusion-free. Then will use the technique in image processing to analyze our data. Our research sperate into two methods of analysis. The first method is remote-Photoplethysmography(rPPG). We will use the existing rPPG method to apply on a human’s forearm, then we’ll use a NIR camera to capture a human’s vessel and propose a revised way to improve the performance of the traditional method. The second method is by Eulerian video magnification to magnify the tiny pulse on our skin, and use optical flow to track the movement. We found out that when occlusion occurs, patients’ pulse will have some sparky and irregular signal compared to when they’re occlusion-free condition. We will describe this phenomenon in numeric values of Signal to Noise Ratio(SNR) and Mean Square Error(MSE). We hope by collecting more patients’ data, we can find out a specific feature to examine dialysis patients' health and replace the original examination which cost lots of medical resources. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T22:27:42Z (GMT). No. of bitstreams: 1 U0001-2808202214031500.pdf: 4547543 bytes, checksum: c604b8bb394bb7ba662eac99e712a40c (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 口試委員審定書 i 致謝 ii 摘要 iii Abstract iv 目錄 vi 圖目錄 viiii 表目錄 xii 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 3 1.2.2 人工瘻管 4 1.2.3 血管阻塞 4 1.4研究動機與簡介 5 1.3 研究內容與本文架構 6 第二章 文獻回顧 7 2.1 非接觸式血流分析 7 2.2 Eulerian影像放大 11 第三章 軟體端之動態影像後處理 13 3.1 遠距光體積變化描紀圖 13 3.2 Eulerian影像放大處理 17 第四章 遠距光體積變化描紀圖分析 22 4.1 傳統遠距光體積方法 22 4.2 遠距光體積投影法 32 第五章 光流法分析 37 5.1 光流法前處理 37 5.1.1 Eulerian影像處理參數設定 37 5.1.2 光流法處理 40 5.2 位移累計分析與影像處理結果 41 5.3 位移時頻分析 43 5.3.1 皮膚遮罩製作 44 5.3.2 平均光流位移紀錄 50 第六章 、影像擷取設備 56 6.1 硬體機構設計 56 6.2 拍攝設備及拍攝格式 59 6.3 拍攝介面及影像格式 62 6.4 病例報告 632 第七章 案例分析 687 7.1 位移累計分析 68 7.2 位移時頻分析 76 第八章 結論與未來展望 89 參考資料 90 圖 1.1 2血液透析示意圖[7] 2 圖 2.1 1、24小時心電圖裝置[9] 7 圖 2.1 2、主成份分析示意圖[20] 9 圖 2.1 3、針對頸部影像血流的可視化[22] 10 圖 2.1 4、人體微血管分布[23] 11 圖 2.2 1、Eulerian顏色增強[29] 12 圖 3.1 1、皮膚光反射模型[35] 14 圖 3.1 2、紅外光鏡頭下拍射出的手臂 17 圖 3.2 1、一維餘弦訊號處理示意圖(α=1) 19 圖 3.2 2 放大倍率因子α與波長λ關係圖 21 圖 4.1 1、血管二值化流程 23 圖 4.1 2、血管骨架提取成果 24 圖 4.1 3、齊次座標系 25 圖 4.1 4、經過單應性矩陣後的轉換 26 圖 4.1 5、血管座標轉換 27 圖 4.1 6、帶有雜訊的訊號示意圖 28 圖 4.1 7、洩漏(leakage)示意圖[48] 29 圖 4.1 8、漢尼函數及其傅立葉轉換[49] 29 圖 4.1 9、訊號經過漢尼視窗後示意圖[48] 30 圖 4.1 10、訊號比示意圖 31 圖 4.2 1、IMF波形範例 33 圖 4.2 2、非血管綠色頻道進行EMD分解結果 34 圖 4.2 3、影像晃動正規化 35 圖 4.2 4、解離出的脈動訊號 36 圖 5.1 1各式濾波器示意圖,(a)0.8-1Hz理想帶通濾波器,(b)175-255Hz理想帶通濾波器,(c)3.6-6.2Hz巴特沃斯帶通濾波器,(d)二階IIR帶通濾波器(本研究使用) 38 圖 5.1 2、受試者A放大影像處理結果(左側為原始影片的連續四幀,右邊則是與之對應經放大後的影像) 39 圖 5.1 3、受試者A光流法動作擷取示意圖 40 圖 5.2 1、受試者A位移累計示意圖 41 圖 5.2 2、colormap 顏色分布 42 圖 5.2 3、受試者A光流法位移圖 43 圖 5.3 1、HSV色彩空間 44 圖 5.3 2、受試者C經由HSV空間所得到的皮膚遮罩 45 圖 5.3 3、雙邊濾波器 47 圖 5.3 4、影像經過雙邊濾波器的差異 47 圖 5.3 5、k-means演算法流程圖[52] 48 圖 5.3 6、群體中心示意圖[53] 49 圖 5.3 7、當k=5時的分群結果 49 圖 5.3 8、皮膚遮罩成果 50 圖 5.3 9、將手臂分成四等份 51 圖 5.3 10、受試者C術前光流法位移紀錄 52 圖 5.3 11、受試者C術後光流法位移紀錄 52 圖 5.3 12、頻普及高斯窗函數示意圖 53 圖 5.3 13、曲線擬合(一) 54 圖 5.3 14、曲線擬合(二) 54 圖 6.1 1、硬體架構示意圖 56 圖 6.1 2、拍攝硬體CAD圖,前凸出的為滑台機構,圓弧狀為受試者手軸放置處 57 圖 6.2 1、HD Webcam C615 59 圖 6.3 1、c#使用者介面 62 圖 6.4 1、治療報告(一) 64 圖 6.4 2、治療報告(二) 65 圖 6.4 3、治療報告(三) 66 圖 7.1 1、受試者A光流法位移圖 70 圖 7.1 2、受試者B光流法位移圖 71 圖 7.1 3、受試者C光流法位移圖 72 圖 7.1 4、受試者D光流法位移圖 73 圖 7.1 5、受試者E光流法位移圖 74 圖 7.1 6、受試者F光流法位移圖 75 圖 7.2 1、受試者A波形折線圖 77 圖 7.2 2、受試者B波形折線圖 78 圖 7.2 3、受試者C波形折線圖 79 圖 7.2 4、受試者D波形折線圖 80 圖 7.2 5、受試者E波形折線圖 81 圖 7.2 6、受試者F波形折線圖 82 表 4.1 1、傳統遠距光體積描記圖於手臂上的結果比較 32 表 5.1 1、eulerian影像參數值 38 表 6.1 1、懷外線發射器規格 58 表 6.2 1、IDS相機規格表 61 表 7.2 1、SNR訊噪比六位受試者之紀錄 84 表 7.2 2、MSE方均差六位受試者之紀錄 86 | - |
dc.language.iso | zh_TW | - |
dc.title | 影像處理於血液透析患者之分析 | zh_TW |
dc.title | Image processing on analysis of dialysis patients | en |
dc.type | Thesis | - |
dc.date.schoolyear | 110-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 陳湘鳳;林峻永 | zh_TW |
dc.contributor.oralexamcommittee | Siang-Fong Chen;Chun-Yeon Lin | en |
dc.subject.keyword | 血液透析,血管阻塞,影像處理,影像放大,遠距光體積變化描紀圖, | zh_TW |
dc.subject.keyword | dialysis,vessel occlusion,image processing,video magnification,remote photoplethysmography, | en |
dc.relation.page | 91 | - |
dc.identifier.doi | 10.6342/NTU202202892 | - |
dc.rights.note | 同意授權(限校園內公開) | - |
dc.date.accepted | 2022-08-30 | - |
dc.contributor.author-college | 工學院 | - |
dc.contributor.author-dept | 機械工程學系 | - |
dc.date.embargo-lift | 2027-08-29 | - |
顯示於系所單位: | 機械工程學系 |
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