進階搜尋


下載電子全文  
系統識別號 U0026-2107201114551100
論文名稱(中文) 以高頻超音波逆散射訊號追蹤腕部神經之運動情形
論文名稱(英文) Motion Tracking of the Median Nerve in the Wrist by High-Frequency Ultrasonic Backscattering
校院名稱 成功大學
系所名稱(中) 資訊工程學系碩博士班
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 99
學期 2
出版年 100
研究生(中文) 謝媺育
研究生(英文) Mei-Yu Hsieh
學號 P76981332
學位類別 碩士
語文別 中文
論文頁數 67頁
口試委員 口試委員-崔博翔
口試委員-黃執中
指導教授-王士豪
中文關鍵字 高頻超音波  腕隧道症候群  位移追蹤  相關係數 
英文關鍵字 High frequency ultrasound  Carpal tunnel syndrome  Motion tracking  Correlation coefficient 
學科別分類
中文摘要 近年來,超音波醫學影像系統的快速發展,超音波影像被頻繁的應用至臨床診斷上,例如藉由超音波影像分析正中神經之資訊結構來診斷腕隧道症候群。然而臨床常用的超音波影像解析度約為毫米範圍,欲提升解析度與測量敏感度,需增加超音波頻率。故本研究使用高頻超音波成像系統,來檢測手指運動與腕部正中神經之位移特性。研究對象為10位健康自願者為實驗對象,測量位置為右手腕皺摺處後7.5mm,設計不同彎曲角度的手指運動,擷取手腕內部組織之逆散射訊號。研究方法為以相關係數來追蹤ROI之移動狀況,使用CPU=7來平行處理迴圈程式部分,並利用兩種不同強度反射子之假體實驗驗證追蹤程式之正確性。在追蹤腕部正中神經之實驗結果發現,手指從伸展至0度到彎曲至90度運動時的正中神經運動軌跡為向左上偏移,其垂直與水平位移量約為6.20mm與3.29mm;在垂直方向,角度與位移變化量、累積位移量的關係為成長指數型態,在水平方向,角度與累積位移量的關係為負指數型態,在總方向,角度與位移變化量、累積位移量的關係為成長指數型態。為降低實驗對象個體差異性所造成不同的結果,故採用比例的方式來探討。在垂直方向,角度與累積位移量佔比的關係為成長指數型態,在水平方向,角度與累積位移量佔比的關係為負指數型態,在總方向,角度與累積位移量佔比的關係為成長指數型態,且角度與累積位移量佔比關係方程式的R2皆高於0.96。本研究,提供了手指彎曲不同角度與正中神經位移方向、位移量之間的變化關係。未來,可應用測量腕隧道症候群病患,根據手指不同的運動狀況,來量測並成像腕部神經的位移,計算其相關係數並評估其位移量,定量腕隧道症候群的嚴重情況。
英文摘要 Ultrasound imaging has been frequently applied to medical diagnoses base on the development of ultrasound medical imaging system recently. The examination of the carpal tunnel syndrome (CTS) via measurement of the median nerve is just application example recently. The resolution of clinical ultrasound images is around mm range. To improve the image resolution and sensitivity, the ultrasound frequency needs to be further increased. In this study, a high-frequency ultrasound system was used to assess the displacement characteristics associated with the finger motion and the median nerve in the carpal tunnel. First, we used two phantoms to verify the motion tracking program. In vivo experiments were performed on the right wrist of 10 healthy volunteers. Backscattering signals were collected and then image ultrasonic images from the level of the wrist crease covering the movements of fingers from extension to flexion at different angles. We search the maximum correlation of ROI using correlation coefficient. Results showed that the slope of the tracking path was approximately the same we designed in phantoms experiments and the path of the median nerve is that shifts in the ulna and palmar direction when fingers from extension to flexion. The variation of displacement, cumulative displacement and cumulative displacement ratio of the median nerve are exponential growth distribution in the total direction and palmar-dorsal direction. The cumulative displacement and cumulative displacement ratio of the median nerve are negative exponential distribution in the ulna-radius direction. In this study, we demonstrated the relationship between the movements of fingers from extension to flexion and the displacement of the median nerve at different angles. Based on these results, we can measure the serious degree of suspected carpal tunnel syndrome, calculate correlation coefficient, track the kinetic information of the wrist, and then evaluate the degree of carpal tunnel syndrome in the future.
論文目次 論文口試委員審定書(中文)..................................I
論文口試委員審定書(英文).................................II
中文摘要................................................III
Abstract..................................................V
誌謝....................................................VII
目錄...................................................VIII
圖目錄...................................................XI
表目錄..................................................XIV



第一章 緒論..............................................1
1.1 前言..............................................1
1.2 研究背景..........................................2
1.3 文獻回顧..........................................3
1.3.1 目前醫療診斷方法與其缺點..........................3
1.3.2 超音波應用腕隧道的發展............................4
1.4 研究目的..........................................7
第二章 理論基礎..........................................9
2.1 超音波簡介........................................9
2.1.1 基本原理..........................................9
2.1.2 反射與折射.......................................10
2.1.3 散射與衰減.......................................12
2.1.4 換能器與聲場.....................................17
2.2 追蹤技術.........................................20
2.2.1 樣版比對法.......................................20
2.2.2 主動式輪廓模型(active contour model).............23
2.3 腕隧道結構.......................................24
第三章 實驗材料與研究方法...............................28
3.1 實驗材料.........................................28
3.1.1 高頻超音波影像系統...............................28
3.1.2 成像與追蹤技術...................................31
3.2 假體製作與追蹤程式驗證...........................34
3.3 腕部正中神經之位移量測...........................36
第四章 結果與討論.......................................38
4.1 假體實驗結果.....................................38
4.1.1 假體I之位移追蹤..................................38
4.1.2 假體II之位移追蹤.................................40
4.2 腕部正中神經之位移結果...........................42
4.2.1 運動軌跡.........................................42
4.2.2 位移變化量.......................................46
4.2.3 累積位移量.......................................49
4.2.4 累積位移量佔比...................................52
4.3 討論.............................................57
第五章 結論與未來工作...................................61
5.1 結論.............................................61
5.2 未來工作.........................................62
參考文獻.................................................64
參考文獻 [1] K. K. Shung, Diagnostic Ultrasound: Imaging and Blood Flow Measurements, Boca Raton, FL: CRC Press, 2006.
[2] G.R. Lockwood, D.H. Turnbull, D.A. Christopher, and F.S. Foster, “Beyond 30 MHz [applications of high-frequency ultrasound imaging],” IEEE Eng. Med. Biol., vol.15, no.6, pp. 60-71, 1996.
[3] D. A. Knapik, B. Starkoski, C. J. Pavlin, and F. S. Foster, “A real time 200 MHz ultrasound B-scan imager,” IEEE Ultrasonics Symposium, vol.2, pp.1457-1460, 1997.
[4] D. A. Christensen, Ultrasonic Bioinstrumentation, New York: Wiley, 1998.
[5] F. S. Foster, C. J. Pavlin, K. A. Harasiewicz, D. A. Christopher, and D. H. Turnbull, “Advances in ultrasound biomicroscopy,” Ultrasound Med. Biol., vol.26, no.1, pp.1-27, 2000.
[6] J. J. Putnam, “A series of cases of paraesthesia, mainly of the hands, of periodic recurrence, and possibly of vasomotor origin,” Archive of Medicine (New York), vol. 4, pp. 147-162, 1880.
[7] S. J. Paget, Lectures on Surgical Pathology, Philadelphia: Lindsay and Blakiston, 1854.
[8] G. S. Phalen, W. J. Gardner, and A. A. La Londe, “Neuropathy of the median nerve due to compression beneath the transverse carpal ligament, “J. Bone Joint Surg. Am., vol. 32A, no.1, pp. 109-112, 1950.
[9] G. S. Phalen, “Spontaneous compression of the median nerve at the wrist,” JAMA-J. Am. Med. Assoc., vol. 145, pp. 1128-1132, 1951.
[10] G. S. Phalen and J. I. Kendrick, “Compression neuropathy of the median nerve in the carpal tunnel,” JAMA-J. Am. Med. Assoc., vol. 164, pp. 524-530, 1957.
[11] D. Simovic and D. H. Weinberg , “Carpal tunnel syndrome,” Arch. Neurol.-Chicago, vol. 57, pp.754-755, 2000.
[12] J. D. Stewart and A. Eisen, “Tinel’s sign and the carpal tunnel syndrome,” Brit. Med. J., vol. 2, pp. 1125-1126, 1978.
[13] J. N. Katz, M. G. Larson, A. Sabra,et al., “The carpal tunnel syndrome: diagnostic utility of the history and physical examination findings,” Ann. Intern. Med., vol. 112, pp. 321-327, 1990.
[14] P. Chen, N. Maklad, M. Redwine, and D. Zelitt, “Dynamic high-resolution sonography of the carpal tunnel,” Am. J. Roentgenol., vol. 168, no.2, pp. 533-537, 1997.
[15] R. Beekman and L. H. Visser, “Sonography in the diagnosis of carpal tunnel syndrome: a critical review of the literature,” Muscle Nerve, vol. 27, no.1, pp. 26-33, 2003.
[16] A. B. Grundberg, “Carpal tunnel decompression in spite of normal electromyography,” J. Hand Surg.-Am.,Vol., vol.8, no.3, pp.348-349, 1983.
[17] I. Duncan, P. Sullivan, and F. Lomas, “Sonography in the diagnosis of carpal tunnel syndrome,” Am. J. Roentgenol., vol.173, pp. 681-684, 1999.
[18] E. Slivestri, C. Martinoli, L. E.Derchi, M. Bertolotto, M. Chiaramondia, and I. Roseberg, “Echotexture of peripheral nerves: correlation between US and histologic findings and criteria to differentiate tendons,” Radiology, vol.197, no.1, pp.291-296, 1995.
[19] D. Lee, M. T. van Holsbeeck, P. K. Janevski, D. L. Ganos, D. M. Ditmars, and V. B. Darian, “Diagnosis of carpal tunnel syndrome: ultrasound versus electromyopathy,” Radiol. Clin. N. Am, vol.37, no.4, pp.859-872,1999.
[20] S. M. Wong, J. F. Griffith, A. C. F. Hui, A. Tang, and K. S. Wong, “Discriminatory sonographic criteria for the diagnosis of carpal tunnel syndrome,” Arthritis Rheum.-US, vol. 46, no.7, pp.1914-1921, 2002.
[21] H. R. Ziswiler, S. Reichenbach, E.Vogelin, L. M. Bachmann, P. M. Viller, and P. Juni, “Diagnostic value of sonography in patients with suspected carpal tunnel syndrome-A prospective study,” Arthritis Rheum.-US, vol.52, no.1, pp.304-311, 2005.
[22] Y. Yoshii, H. R. Villarraga, J. Henderson, C. Zhao, K. N. An, and P. C. Amadio, “Ultrasound assessment of the displacement and deformation of the median nerve in the human carpal tunnel with active finger motion,” J. Bone Joint Surg. Am., vol. 91, no.12, pp.2922-2930, 2009.
[23] M. H. M. van Doesburg, Y. Yoshii, H. R. Villarraga, J. Henderson, S. S. Cha, K. N. An, and P. C. Amadio, “Median nerve deformation and displacement in the carpal tunnel during index finger and thumb motion,” J. Orthop. Res., vol.28, no.10, pp.1387-1390, 2010.
[24] D. A. Christensen, Ultrasonic Bioinstrumentation. New York: Wiley, 1988.
[25] K. K. Shung, M. B. Smith, and B. M. W. Tsui, Principles of Medical Imaging. Academic Press, San Diego, 1992.
[26] R. C. Molthen, P. M. Shankar, and J. M. Reid, “Characterization of ultrasonic B-scans using non-Rayleigh statistics,” Ultrasound Med. Biol., vol.21, no.2, pp.161-170, 1995.
[27] V. Dutt and J. F. Greenleaf, “Ultrasound Echo Envelope Analysis Using a Homodyned K Distribution Signal Model,” Ultrasonic Imaging, vol.16, no.4, pp.265-287, 1994.
[28] J. A. Jensen, Estimation of Blood Velocities using Ultrasound, Cambridge University Press, 1996.
[29] J. V. Hajnal, D. L. G. Hill, and D. J. Hawkes, Medical Image Registration. Boca Raton, CRC Press, 2001.
[30] M. S. Lew, N. Sebe, and T. S. Huang, “Improving Visual Matching,” IEEE Conference on Computer Vision and Pattern Recognition(CVPR), vol.2, no., pp.58-65, 2000.
[31] J. L. Myers and A. D. Well, Research Design and Statistical Analysis, Lawrence Erlbaum Associates, 2003.
[32] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models,” Int. J. Comput. Vision, vol.1, no.4, pp.321-331, 1988.
[33] D. J. Williams and M. Shah, “A fast algorithm for active contours and curvature estimation,” CVGIP Image Understanding, vol.55, pp.14-26, 1992.
[34] K. M. Lam and H. Yan, “Fast greedy algorithm for active contours,” Electron. Lett., vol.30, pp.21-23, 1994.
[35] K. Monagle, G. Dai, A. Chu, R. S. Burnham, R. E. Snyder, “Quantitative MR Imaging of Carpal Tunnel Syndrome,” Am. J. Roentgenol, vol.172, no.6, pp. 1581-1586, 1999.
[36]馮琮涵與陳金山, 人體解剖學 Human Anatomy. 偉明圖書有限公司,2006.
[37] “University of Maryland- Medical Center,” http://www.umm.edu/ patiented/articles/how_carpal_tunnel_syndrome_diagnosed_000034_7.htm, 2010.
[38] “The Steadman Clinic,” http://thesteadmanclinic.com/hand, 2011.
[39] “Budding neurosurgeon’s e-campus,” http://www.eneurosurgery.com/ brachialplexus.html, 2011
[40] “Blass,” http://blass.com.au/definitions/bicipital, 2011.
[41] J. J. Brooks, J. R. Schiller, S. D. Allen, and E. Akelman, “Biomechanical and anatomical consequences of carpal tunnel release,” Clin. Biomech., vol. 18, no. 8, pp.685-693, 2003.
[42] J. R. Doyle and M. J. Botte, Surgical Anatomy of the Hand and Upper Extremity. Lippincott Williams & Wilkins, 2003.
[43] “OneCrutch,” http://www.onecrutch.com/carpal.html, 2011.
[44] “MathWorks,” http://www.mathworks.com/help/toolbox, 2011.
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2014-08-02起公開。
  • 同意授權校外瀏覽/列印電子全文服務,於2015-08-02起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw