透過您的圖書館登入
IP:18.188.61.223
  • 學位論文

人體組織特性之有限元素模型

Finite Element Modelling of Human Soft Tissue

指導教授 : 顏炳郎

摘要


乳癌是為目前女性發生率最高的癌症,但早期的檢測、治療可以增加乳癌的治癒率。腫瘤的硬度與其良性和惡性密切相關,硬度則是腫瘤與組織之間的比較。在本文中,為了腫瘤僵硬度預測,建立了乳房有限元模型,而有限元模型將與力量探測實驗相互比較,將仿體視為超彈性材料,並且對於此材料進行單軸拉伸試驗,取得形成超彈性體所需之參數。在壓痕分析的結果上得到此模型與實驗上比較後,此模型具備一定程度準確性,在壓痕分析中比對3 mm至5 mm深度之力量回饋,所得到的RMSE數值分別為0.07 N、0.19 N、0.22 N,而在仿體橫向探測模擬中,選取適當的摩擦係數,下壓3 mm至5 mm深度並橫移之力量回饋,與機械手臂實驗數據相比,所得到的RMSE值分別為0.22 N、0.54 N、0.38 N。

並列摘要


Breast cancer is the highest incidence of cancer in women, but early detection and treatment can increase the cure rate of breast cancer.The stiffness of a tumor is closely related to its benign and malignant, and the hardness is a comparison between tumor and tissue. In this paper, for the prediction of tumor stiffness, a breast finite element model is established, and the finite element model will be compared with the force detection experiment, the breast phantom is regarded as a hyperelastic material, and the uniaxial tensile test was used to obtain the parameters describing the hyperelastic model of soft tissue, after the model is compared with the experimental results of the indentation analysis. The model demonstrates a good accuracy, and the force feedback of the depth of 3 mm to 5 mm is compared in the indentation analysis, the RMSE values are 0.07 N, 0.19 N, and 0.22 N, respectively. In the simulation of the lateral exploration, the appropriate friction coefficient is selected, the RMSE values are 0.22 N、0.54 N、0.38 N, respectively.In the simulation of the lateral exploration experiment, the appropriate friction coefficient is selected. Compared with the experimental data, the RMSE values obtained by pressing down the depth of 3 mm to 5 mm are 0.22 N, 0.54 N, and 0.38 N, respectively.

參考文獻


[1] Gilbertson, M. G., and Anthony, B. W. 2013. An ergonomic, instrumented ultrasound probe for 6-axis force/torque measurement. in Engineering in Medicine and Biology Society (EMBC). 140–143.
[2] 徐筱晴。2015。乳房腫瘤之形狀力學模型建立。 碩士論文。台北:台灣大學生物產業機電工程學系
[3] H. Liu, D. Noonan, Y. Zweiri, K. Althoefer, L. Seneviratne. 2007. The Development of Nonlinear Viscoelastic Model for the Application of Soft Tissue Identification. Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst. 208-213.
[4] Samani A, Bishop J, Yaffe MJ, Plewes DB. 2001. Biomechanical 3D finite element modeling of the breast using MRI data. IEEE Trans Med Imaging. 20:271-279.
[5] F. S. Azar, D. N. Metaxas, and M. D. Schnall. 2000. A finite element model of the breast for predicting mechanical deformations during biopsy procedures. in Proc. IEEE Workshop Mathematical Methods in Biomedical Image Analysis. 38–45.

延伸閱讀