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研究生: 林家煌
Lin, Jia-Huang
論文名稱: 以動態追蹤技術評估腕隧道症候群患者腕部超音波影像之正中神經動態軌跡
Assessment of Kinetic Trajectory of the Median Nerve from Wrist Ultrasound Images in Patients with Carpal Tunnel Syndrome by Motion Tracking Technique
指導教授: 王士豪
Wang, Shyh-Hau
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2017
畢業學年度: 105
語文別: 英文
論文頁數: 59
中文關鍵詞: 腕隧道症候群正中神經動態追蹤腕部超音波
外文關鍵詞: carpal tunnel syndrome, median nerve, motion tracking, wrist ultrasound
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  • 腕隧道症候群是一種常見在腕部正中神經長期受壓迫所造成的神經疾病。病理學研究顯示在腕隧道症候群患者的手腕滑膜結締組織產生了纖維化的現象,可能改變正中神經的運動情形,先前的研究結果顯示正常人的正中神經在手指運動過程中會在橈骨側往尺骨側呈現S型趨勢運動,然而先前研究所得到之結果並未真正與腕隧道症候群患者進行比較。因此,本研究目的在於使用三種不同之動態追蹤演算法(NCC、ABST、OFT)來分析腕隧道患者與正常人在手指運動過程中正中神經軌跡希望藉此比較出正常人與病患之間神經運動軌跡的差異。使用商用超音波儀器搭配12MHz的探頭分別量測二十位平均年齡為56.8±8.6歲且腕部無相關疾病與三十位平均年齡為56.6±12.6歲並患有腕隧道症候群志願者的手腕。結果顯示當手指彎曲時,正常人之正中神經在移往尺骨方向時,其移動軌跡與S型趨勢的相關性為高度相關(R^2≥0.7) ,而患者的相關性較正常人低(R^2≤0.5)。而在正中神經的位移量方面,由三種不同的動態追蹤方法所測量得到的結果分別是正常人2.69mm, 2.89mm,2.64mm,患者1.41mm,1.59mm,1.32mm。兩者間有顯著差異,本篇研究所得到正常人病患與病患之正中神經動態軌跡差異提供了一個可能被延伸應用於輔助診斷腕隧道症候群的可行性方法。

    Carpal tunnel syndrome (CTS) is a wrist disease, which is caused by the median nerve oppressed chronically. CTS patients are usually associated with the fibrosis of subsynovial connective tissue, which may change the median nerve movement. The previous studies have measured that the kinetic trajectory of median nerve in normal subjects following sigmoidal tendency in ulnar-radial direction during the finger movement. However, the motion tracking techniques used in previous studies may lose some information of displacement and cost much time to execute. In addition that the results obtained in the previous studies were not really compared with CTS patients. Therefore, the purpose of this study is to compare the advantages and disadvantages in different motion tracking techniques which are normalized cross correlation (NCC), Adaptive Bayesian speckle tracking (ABST), and optical flow tracking (OFT), and use them to analyze the kinetic trajectory of the median nerve during the fingers movement in CTS patients to compare with normal people. This study used a commercial ultrasound system with 12MHz probe to scan 20 volunteers without related diseases whose age are 56.8 ± 8.6 and 30 CTS patients whose age are 56.6 ± 12.6. The tracking techniques was verified by displacement of median nerve simulated by phantom. The results of the phantom experiment shown that the results tracked by NCC were closest to reality displacement (Slope: 0.984, 0.978, and 0.964). OFT has the fastest execution time in the three tracking methods (average execution time: 5.285±0.26 seconds), and ABST has the longest execution time in the three tracking methods (average execution time: 115.34±2.88 seconds). The results of human experiment shown that the kinetic trajectory from normal subjects followed sigmoidal tendency (R^2≥0.7), whose correlation coefficient is higher than the kinetic trajectory from CTS patients (R^2≤0.5). The maximum displacement of median nerve in normal subjects (2.69 mm, 2.89 mm, 2.64 mm) calculated by NCC, ABST, and OFT were higher than in CTS patients (1.41 mm, 1.59 mm, 1.32 mm). The difference in the kinetic trajectory of the median nerve between the normal people and the CTS patient in this study provides a feasible method that may be extended to assist in the diagnosis of CTS.

    摘要….. I ABSTRACT II 致謝….. IV CONTENT V LIST OF FIGURES VII LIST OF TABLES IX 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 13 2.3 Motion Tracking techniques 15 2.3.1 Template matching method…………………………………………………..15 2.3.2 Normalized cross correlation…………………………………………………15 2.3.3 Bayesian speckle tracking…………………………………………………….16 2.3.4 Optical flow tracking………………………………………………………….18 2.4 Anatomical structure of carpal tunnel 19 CHAPTER 3 MATERIALS AND METHODS 22 3.1 Tracking technique 22 3.1.1 Normalized Cross Correlation………………………………………….......22 3.1.2 Bayesian Speckle Tracking……………………………………………….....24 3.1.3 Adaptive Bayesian Speckle Tracking (ABST)…………………………..…26 3.1.4 Optical flow tracking (OFT)………………………….………………..……29 3.2 Verification of tracking techniques 31 3.3 Wrist measurement with ultrasound 34 CHAPTER 4 RESULTS AND DISSCUSSION 38 4.1 Algorithm verification with phantom 38 4.2 Motion tracking of median nerve in wrist 44 4.3 Discussion 52 CHAPTER 5 CONCLUSIONS 54 5.1 Conclusions 54 5.2 Future works 55 REFERENCES 56

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