C-arm影像導引系統於臨床椎弓螺釘植入之應用與改良

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：40

、訪客IP：3.15.18.157

姓名

謝仁懋(Alex Tse) 查詢紙本館藏

畢業系所

生物醫學工程研究所

論文名稱

C-arm影像導引系統於臨床椎弓螺釘植入之應用與改良
(Clinic pedicle screw insertion trials and system improvement of a C-arm image navigation system)

相關論文

★ 以擠製冷卻成型法結合相分離法製作神經再生用多孔性導管	★ 整合可調式阻力之手足復健機研究
★ 應用於肝腫瘤治療之超音波影像輔助機械臂HIFU燒灼實驗系統	★ 顱顏整型手術用植入物之設計與製作
★ 電腦輔助骨科手術用規劃及導引系統	★ 遠端遙控機械手臂腹腔鏡手術系統
★ 頭部CT與MR影像之融合	★ 手術用影像導引機械人定位及鑽孔系統
★ 機器人校正與醫學影像導引定位應用	★ 顱顏手術用規劃及導引系統
★ 醫學用超音波影像導引系統	★ 應用3D區域成長法於腦部磁共振影像之分割
★ 腦部手術用導引系統之方位校準及腦瘤影像分割	★ 超音波影像即時震波導引
★ 腫瘤偵測與顱顏骨骼重建	★ 骨科手術用C-arm影像輔助規劃及導引系統

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

C-arm影像輔助手術導引系統可使用兩張C-arm影像的條件下精確得知骨骼與手術器械的相對位置，具有減低輻射線的暴露量、提升手術品質、縮短新進醫師學習曲線等優點。因此本研究以實驗室既有之C-arm導引系統為基礎針對脊椎手術臨床需求進行分析與系統改良。
C-arm導引系統包含影像處理、座標轉換與X光投影模式建構等。系統透過影像處理方法自動偵測C-arm校正器上大、中、小型標記在影像上的座標以供影像校正與座標對正使用。本研究改良大、小型標記之影像辨識方法，提出高通濾波法萃取大鋼珠輪廓、自適應門檻值法分割小鋼珠影像，針對臨床所取得之98張C-arm影像進行測試。結果顯示大型標記之整體辨識率由原先的62%提升至98%，小型標記辨識率75%以上的影像則由35張增加至80張，而且沒有辨識率低於60%之影像。
又C-arm影像拍攝與擷取過程，病人的呼吸會造成目標病灶與C-arm影像校正器相對位置的改變。正確的X光投影模式必須在C-arm設備拍攝影像瞬間紀錄病患身上與C-arm影像校正器上DRF的座標值。本文提出一種手術導引系統之X光影像同步校正方法，該方法包含四個步驟：1.量測影像成像與輸出時間差、2.取得座標轉換關係、3.測量影像相似性、4.重建影像與座標轉換關係。電腦端偵測影像更新時依事先量測的輸出延遲時間取拍攝瞬間的座標關係，解決影像拍攝與擷取過程病人呼吸造成投影模式錯誤的問題。

摘要(英)

C-arm guidance system is developed by integrating image processing, coordinate transformation and projection model estimation. Only two C-arm images are required to compute the orientations and positions of the targets. The locations of surgical instruments are also real-time shown on the computer displayed C-arm images, which enable the surgeon to move surgical tools accurately and safely to the target for following treatment. It also reduces radiation exposure during the operation.
The system automatically detects coordinates of the marker on the C-arm image by image processing techniques. Those markers are used in image distortion and registration. If the number of being recognized markers could not exceed the system requirements, an additional image is required. Therefore, the level of the recognition rate will affect the ease of use of the guidance system.
To improve the successfully recognition rate we analysis 98 C-arm images obtained from clinical try. The overall recognition rate of large marker is increased from 62% to 98%. As for small marker, the quantity of images which recognition rate above 75% is increased from 35 to 80. And recognition rate of all the images are higher than 60%.
Due to patient’s breathing, the relative position between C-arm image calibrator and patient is changed during the process of image capture. Using non-synchronized images and coordinate data will cause an incorrect estimation of projection model. We develop a kind of X-ray images synchronized registration method used in surgical guidance system, the method includes four steps: 1. Estimate the latency of fluoroscopic imaging. 2. Continuously obtain relative position between C-arm image calibrator and patient. 3. Measuring image similarity. 4. Reconstruct the relation between images and coordinate transformation. When the C-arm image is refreshed, software would automatically choose a transformation that has a timestamp prior to pre-measured latency. It solves the problem that image and coordinate are non-synchronized.

關鍵字(中)

★ C-arm
★ X光偵測
★ 影像辨識
★ 脊椎手術
★ 手術導引

關鍵字(英)

★ Spinal Surgery
★ C-arm
★ Surgical Navigation
★ X-ray detection
★ Pattern Recognize

論文目次

摘要 I
Abstract II
目錄 III
圖目錄 V
表目錄 VIII
第1章緒論 1
1-1 研究動機 1
1-2 文獻回顧 1
1-3 研究方法簡介 2
第2章系統架構 3
2-1 硬體架構 3
2-1-1 C-arm影像校正器 3
2-1-2 光學定位系統 4
2-2 軟體開發環境 5
2-3 系統運作流程 5
第3章影像處理與定位方法 7
3-1 系統變更項目總覽 7
3-2 大鋼珠辨識 8
3-3 影像對位方法 13
3-4 小鋼珠辨識 14
3-4-1 搜尋方法與流程 14
3-4-2 二值化演算法 16
3-4-3 演算法效果比較 17
3-5 C-arm影像變形校正 19
3-5-1 計算影像變形的數學模型 19
3-5-2 雙線性內插 20
3-6 座標系統定義與C-arm投影模式 20
3-7 同步擷取C-arm影像與DRF轉換矩陣 23
3-7-1 偵測X-ray之方法 24
3-7-2 C-arm影像輸出延遲量測方法 26
3-7-3 同步化擷取方法 28
3-8 路徑規劃方法 28
第4章實驗結果與討論 31
4-1 影像處理 31
4-1-1 大鋼珠辨識 31
4-1-2 小鋼珠辨識 36
4-1-3 變形校正 41
4-1-4 發射源計算穩定性測試 44
4-2 C-arm影像輸出延遲測試 45
4-3 系統精度實驗 46
4-3-1 模型實驗 46
4-3-2 人體實驗 48
4-4 誤差分析 50
4-4-1 C-arm校正器鋼珠加工與量測誤差 51
4-4-2 C-arm校正器DRF基座變形 53
4-4-3 影像對位誤差 54
第5章結論與未來展望 55
5-1 結論 55
5-2 未來展望 55
參考文獻 57

參考文獻

[1] Eyke, JC., Ricciardi, JE., Roesch, W., Whitecloud III, TS., “Computer-Assisted Virtual Fluoroscopy”, The University of Pennsylvania Orthopaedic Journal,vol.15, pp. 53–59, 2002
[2] Guoyan, Z., Xiao, D., “Robust automatic detection and removal of ﬁducial projections in ﬂuoroscopy images: An integrated solution”, Medical Engineering & Physics., Vol31, Issue 5, p 571–580, 2009
[3] Guoyan, Z., Xiao, D., Paul, A.G., et. al., “Automated detection and segmentation of cylindrical fragments from calibrated C-arm images for long bone fracture reduction”, Computer Methods and Programs in Biomedicine, Vol.87, Issue 1,pp.1-11,2007.
[4] Hufner, T., Kendoff, D., Citak M., Geerling, J. and Krettek, C.,“Precision in orthopaedic computer navigation”, Orthopade, Vol.35, 1043-1055, 2006.
[5] Johnson, HJ., Christensen, GE., “Landmark and intensity-based, consistent Thin-Plate Spline Image Registration”, IPMI, Vol. 2082, p. 329-343.
[6] Kainz, B., Grabner, M., Ruther, M., “Fast marker based C-arm pose estimation.”, Proceedings of the 11th international conference on medical image computing and computer assisted interventions (MICCAI’08), Part II, p. 652–659, 2008
[7] Kendoff, D., Citak, M., Hufner, T., Chaudhary, S. and Krettek, C., “Current concepts and applications of computer navigation in orthopedic trauma surgery”, Central European Journal of Medicine, 392-403, 2007.
[8] Liu, RR., Rudin, S., Bedarek, DR., “Super-global distortion corrections for a rotational C-arm X-ray image intensiﬁer.” Med Phys,Vol 26,pp.1802–10,1999
[9] Livyatan, H., Yaniv, Z. and Joskowicz, L., “Robust automatic C-arm calibration for fluoroscopy-based navigation: a practical approach” Proc 5th Int. Conf. on Medical Image Computing and Computer-Aided Intervention, MICCAI’’2002, October 2002, Tokyo, Japan.
[10] Mobbs, RJ., Sivabalan, P., Li, J., “Minimally invasive surgery compared to open spinal fusion for the treatment of degenerative lumbar spine pathologies.” ,Journal of Clinical Neuroscience. ,2012
[11] Nowitzke, A., Wood, M., Cooney, K., “Improving accuracy and reducing errors in spinal surgery-a new technique for thoracolumbar-level localization using computer–assisted image guidance”, The Spine Journal 8,p 597–604 ,2008
[12] Rampersaud, YR., Foley, KT., Shen, AC., Williams, S., Solomito, M., ” Radiation exposure to the spine surgeon during fluoroscopically assisted pedicle screw insertion.”, Spine (2000),Vol.25, Issue 20, 2637-2645
[13] Smith, L., Pleasance, M., Seeton, R., Archip, N., Rohling, R., “Automatic detection of ﬁducial markers in ﬂuoroscopy images for on-line calibration.”,Med Phys,Vol 32,pp.1521–3,2005.
[14] 王舜民, “骨科手術用C-arm影像輔助規劃及導引系統,” 碩士論文, 中央大學機械工程研究所, 2002.
[15] 吳吉春, 王舜民, 顏兆萱等, “骨科手術用 C-arm 影像輔助導引系統之發展,” 中華民國九十二年度醫學工程年會論文集, pp. 44-45, 2003.
[16] 范紀偉, “應用於髖關節表面重建手術之 C-arm 影像輔助導引系統,” 碩士論文, 中央大學機械工程研究所, 2007.
[17] 楊遠祥, “應用於股骨轉子間骨折之 C-arm based 手術導引系統,” 碩士論文, 中央大學機械工程研究所, 2005.

指導教授

曾清秀(Ching-Shiow Tseng)

審核日期

2012-7-17

推文