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系統識別號 U0026-2108201615215900
論文名稱(中文) 以三維動態追蹤技術評估腕部超音波影像之正中神經動態軌跡
論文名稱(英文) Assessment of Kinetic Trajectory of Median Nerve from Wrist Ultrasound Images Using 3D Motion Tracking Technique
校院名稱 成功大學
系所名稱(中) 資訊工程學系
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 104
學期 2
出版年 105
研究生(中文) 柳冠宇
研究生(英文) Kuan-Yu Liu
學號 P76031153
學位類別 碩士
語文別 英文
論文頁數 61頁
口試委員 指導教授-王士豪
口試委員-孫永年
口試委員-郭榮富
口試委員-黃執中
口試委員-林奕勳
中文關鍵字 腕隧道症候群  正中神經  三維動態追蹤  腕部超音波 
英文關鍵字 carpal tunnel syndrome  median nerve  3D motion tracking  wrist ultrasound 
學科別分類
中文摘要 腕隧道症候群是一種源自於日常生活中手部運動對周邊神經遭長期壓迫所造成的疾病,其症狀有手部感覺異常、麻痺、神經根痛。由於在罹患腕隧道症候群患者的手腕滑膜結締組織中產生了纖維化的現象,因此滑膜結締組織結構上的變化改變了正中神經運動的情形,先前的研究曾測量對正中神經二維位移與手指運動的相互關係,並驗證其診斷腕隧道症候群的檢測能力。然而過去研究正中神經的二維動態軌跡只能看出部分軌跡的資訊,正中神經的三維動態軌跡資訊從未被討論過。因此,本研究目的在於發展一套三維動態追蹤技術的演算法來分析正中神經三維軌跡運動與手指運動的相互關係。利用商用超音波儀器搭配12MHz的探頭量測十位腕部無相關疾病的志願者的手腕,其平均年齡為24.8 ± 3.2歲。受試者須以手掌向上的伸出姿勢進行超音波掃描,同時前臂會被固定在客製化的平台上。掃描的時候超音波探頭會固定在客製化的夾具上並藉由馬達來做移動,同時間以個人電腦控制旋轉馬達帶動受試者手指彎曲,彎曲角度從0度到90度,掃描範圍腕溝紋下0mm到10mm間,最後利用取得連續的B-mode影像來建立正中神經的三維模型和三維影像。量測方法又分為靜態量測和動態量測。結果顯示靜態量測比動態量測更適合做三維軌跡追蹤。結果顯示當手指彎曲時,正中神經在移往尺骨方向時,其移動軌跡呈現S型趨勢(R平方大於等於0.5) 。而在三維動態軌跡中,當手指彎曲時正中神經會往尺骨跟掌心跟手臂方向移動,其位移量分別是4.54mm, 0.51mm, 3.24mm。本篇研究發展一套以互相關係數及貝氏理論為基礎的三維追蹤演算法及一個可行性的方法來減少量測超音波位移的誤差。其建立的正中神經三維動態軌跡提供了一個可能被延伸應用於腕隧道症侯群的可行性方法。
英文摘要 Carpal tunnel syndrome (CTS) is a wrist disease, caused by a compressed median nerve in the wrist from daily hand motions, which causes paresthesia, numbness and radicular pain in the hand. Because of the fibrosis of subsynovial connective tissue surrounding median nerve in the wrists of patients with CTS, the 2-dimensional (2D) displacement of median nerve during fingers motions was explored to aid the diagnosis of the CTS. Nevertheless, the studies of the 3-dimensional (3D) kinetic trajectory of the median nerve, which could provide more detailed information for diagnosing CTS is deficient. This study developed an algorithm to analyze the 3D kinetic trajectory of median nerve during fingers motion. A series of ultrasound B-mode images of the wrist were acquired by using a commercial ultrasound system equipped with a 12MHz linear array. Measurements were performed with the right wrist of 10 asymptomatic volunteers in 24.8 ± 3.2 years old. Each participant was asked to outstretch the right arm with the palming up and the elbow flexing to 90° with the forearm during each experiment. The forearm was fixed to the custom-made platform. The measured position was at the level of wrist crease. The ultrasound probe was fixed on a customized stepping motion stage to measure the B-mode images at a different fingers flexion angle on the wrist to reconstruct 3D images and models. There are two measurements: static measurement and dynamic measurement. The results show that static measurement is more suitable than dynamic measurement for 3D motion tracking. Median nerve tended to move toward to ulnar-palmar-proximal direction during fingers flexion. The maximum displacements of median nerve were 4.54mm, 0.51mm, and 3.24mm corresponding to ulnar-radial, palmar-dorsal, and proximal-distal. Kinetic trajectory followed sigmoidal tendency (R square is more than or equal to 0.5 ) in ulnar-radial direction. This study develops a 3D motion tracking method based on NCC and Bayesian for analyzing 3D kinetic trajectory of median nerve and a feasible method to reduce the error which is the displacement of median nerve during finger flexion. 3D Kinetic trajectory during finger flexion could be applied to assess CTS extensively.
論文目次 CONTENT
論文口試委員審定書 I
論文口試委員審定書 II
摘要…. III
ABSTRACT IV
誌謝…. VI
CONTENT VII
LIST OF FIGURES IX
LIST OF TABLES XI
CHAPTER 1 INTRODUCTION 1
1.1 Foreword 1
1.2 Research background 2
1.3 Related research 3
1.3.1 Assessment methods of CTS in clinical diagnosis……………………………3
1.3.2 Application of CTS in Ultrasound image…………………………………….5
1.4 Motivation and objective 8
CHAPTER 2 BACKGROUND 10
2.1 Fundamentals of ultrasound 10
2.1.1 Fundamentals of acoustic wave………………………………………………10
2.1.2 Reflection and refraction……………………………………………………..10
2.1.3 Attenuation…………………………………………………………………....11
2.2 Ultrasonic transducers 14
2.3 Motion Tracking techniques 16
2.3.1 Template matching method…………………………………………………..16
2.3.2 Normalized cross correlation…………………………………………………16
2.3.3 Bayesian speckle tracking…………………………………………………….17
2.4 Anatomical structure of carpal tunnel 19
CHAPTER 3 MATERIALS AND METHODS 21
3.1 Tracking technique 21
3.1.1 2D Normalized Cross Correlation…………………………………………...21
3.1.2 3D Normalized Cross Correlation…………………………………………...22
3.1.3 2D Bayesian Speckle Tracking……………………………………………….23
3.1.4 Adaptive Bayesian Speckle Tracking (ABST)………………………………26
3.1.5 3D Normalized Cross Correlation Algorithm………………………………28
3.2 Reconstruction of 3D image 31
3.2.1 Reconstruction of 3D image with inner information……………………….32
3.3 3D Graphical User Interface system 34
3.4 Verification of 3D tracking technique 35
3.5 Wrist measurement with ultrasound 39
CHAPTER 4 RESULTS AND DISSCUSSION 43
4.1 Algorithm verification with phantom 43
4.2 Motion tracking of median nerve in wrist 46
4.3 3D Median Nerve Graphical User Interface system 53
CHAPTER 5 CONCLUSIONS 56
5.1 Conclusions 56
5.2 Future works 56
REFERENCES 58
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