臺灣博碩士論文加值系統

人類因為擁有雙眼所以可以看見事物，並針對所見之事物傳達給大腦進行處理，並對身體下達處理反應，但相對於若沒有標準量、尺度的事情則會發生些許誤差以及不同人所判斷的差異，並在現代科技的發展，在各領域中皆有個系統所拍攝的龐大影像，例如工業檢測、醫學影像等...，這些影像如果使用人眼和大腦去判斷則需耗時費事，如藉由其他可程式並自動化判斷則可節省許多時間。
　　對於急性或是慢性傷口的評估管理目前是臨床醫生實施治療方式得一個重要的關鍵依據，目前醫療單位常用的傷口面積量測方法及工具常有沒效率、不安全、不準確和無法追溯性等問題。
　　本論文實現了一套結合TOF測距晶片及BLE藍芽晶片與智慧型手持裝置，透過測距晶片將計算所需資訊傳回手持裝置並同時手持裝置拍攝照片後自動或是手動圈選照片中需測量區域並配合影像處理中的二值化(Thresholding)、邊緣偵測(Scharr)、尋找輪廓(FindContours)將傷口面積圈選出來並配合距離資訊將實際傷口所涵蓋的面積回饋給使用者並將資料儲存進相片方便往後調閱觀察。
　　研究針對45筆不同的傷口並對五位實驗者分別進行醫院現行的測量手法以及利用本系統進行測量並以醫學研究中常使用的軟體Image-J所測量的面積為標準值進行比較，傳統測量手法累積平均誤差為57%並本系統所測量的累積平均誤差為11%。

Human beings have eyes to see things, and the information will be transported to brain for processing then make comment to body for acting. For those things are not having standard scales, there might happens some measuring deviation caused by judgement from different people. For the technology development nowadays, every field have huge image data shot by system, for example: industrial detection, medical images……etc. It will take so many times if we use human eyes and rains to judge these images, but we can save bunch of time by using computer programing and automatic judging system.
The evaluation management of acute or chronic wound is the key basis of the clinical treatment for doctors to apply the therapy. The wound area measurement technology and tooling now using in medical unit is often considered low efficiency, not safe, low accuracy and untraceable.
This thesis fulfill a system combined with TOF distance detection chip, BLE blue tooth chip and smart handheld device. By using the function of distance detection chip to calculate the needed information and pass to handheld device, and using the handheld device to take photos then auto/manually circling the area need to be detected in the photo at the same time, we can feedback the actual wounded area to users for data storage and observation by using image processing method such as: thresholding, scharr, find contours.
This research focus on 45 different wounded area data and 5 different subjects by using the measurement method that medical unit now using and our method separately and using the measuring system Image-J as standard for comparing judgement. The result shows that the accumulative average error of traditional way of measuring is 57% and our method is only 11%.

目錄

摘　要 i
ABSTRACT ii
誌謝 iii
目錄 iv
表目錄 vii
圖目錄 viii
第一章緒論 1
1.1 前言 1
1.1.1 傷口面積的測量 1
1.1.2測量工具的現況 2
1.2 研究動機與目的 2
1.3 論文架構 4
第二章文獻探討 5
2.1 現行的傷口面積測量工具 5
2.1.1 長乘寬(標準尺)測量法 5
2.1.2 網格測量法 7
2.1.3 Smith＆Nephew的Visitrak系統 8
2.1.4 數位攝影測量 9
2.2手持式雷射測距裝置 10
2.2.1 距離測量 10
2.2.2 雷射原理 11
2.2.3 雷射距離測量 13
2.2.4 面積測量 15
第三章實驗架構 21
3.1 系統流程介紹 21
3.1.1 雷射測距傳感器單元 22
3.1.2 無線傳輸單元 24
3.1.3 元件固定機殼 28
3.1.4 距離及運算整合單元 28
3.2 表面傷口面積測量的系統模型 29
3.2.1 測量系統的距離測量方案 30
3.2.2 鏡頭視角及像素計算方案 31
3.3.1 iOS系統架構 34
3.3.2 APP系統架構 35
3.4 OpenCV 36
3.5 系統安裝及功能驗證 38
3.5.1 手持裝置單元功能驗證 38
3.5.2測距模組功能驗證 39
3.6 系統效能實驗設定及步驟 39
3.6.1 系統係數驗證 39
3.6.2 系統效能驗證 41
3.6.3 實際傷口效能驗證 42
第四章實驗架構結果與討論 45
4.1 系統係數驗證結果 45
4.2 系統效能驗證結果 47
4.2.1 距離效能驗證的初步結果 48
4.2.2 面積效能驗證的綜合結果 52
4.2.3 距離與面積量測結果的綜合討論 62
4.3 實際傷口效能驗證結果 65
4.3.1標準尺測量法與軟體圈選的效能驗證 65
4.3.2標準尺測量法、軟體圈選對Image-J標準值的效能驗證 66
第五章結論 68
5.1 系統可行性說明 68
5.2 未來研究方向 69
參考文獻 71
附錄 74
A. 系統效能驗證之標準圖形數據 74
A.1近焦距離160mm的基礎實驗之數據 74
A.2遠焦距離320mm的基礎實驗之數據 75
B. 系統安裝及系統係數基礎實驗驗證結果 76
B.1近焦距離160mm的正方形標準圖形實驗之數據 76
B.2近焦距離160mm的等腰直角三角形標準圖形實驗之數據 77
B.3近焦距離160mm的圓形標準圖形實驗之數據 78
B.4中焦距離240mm的正方形標準圖形實驗之數據 79
B.5中焦距離240mm的等腰直角三角形標準圖形實驗之數據 80
B.6中焦距離240mm的圓形標準圖形實驗之數據 81
B.7遠焦距離320mm的正方形標準圖形實驗之數據 82
B.8遠焦距離320mm的等腰直角三角形標準圖形實驗之數據 83
B.9遠焦距離320mm的圓形標準圖形實驗之數據 84
C. 系統效能驗證之實際傷口數據 85
C.1實驗者1的實際傷口效能驗證實驗之數據 85
C.2實驗者2的實際傷口效能驗證實驗之數據 86
C.3實驗者3的實際傷口效能驗證實驗之數據 87
C.4實驗者4的實際傷口效能驗證實驗之數據 88
C.5實驗者5的實際傷口效能驗證實驗之數據 89

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