請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52579
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 顏炳郎(Ping-Lang Yen) | |
dc.contributor.author | Hsiao-Ching Hsu | en |
dc.contributor.author | 徐筱晴 | zh_TW |
dc.date.accessioned | 2021-06-15T16:19:14Z | - |
dc.date.available | 2020-08-28 | |
dc.date.copyright | 2015-08-28 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-08-17 | |
dc.identifier.citation | Amos, B., C. Hess, C. Cronin, and C. Tank. 2014. Clinical Breast Examination. Providence Health Services. Available at: http://appsor.providence.org/healthlibrary/ContentViewer.aspx?hwid=tv7408#tv7412. Bajwa, I. S., M. S. Naweed, M. N. Asif, and S. I. Hyder. 2009. Feature based image classification by using principal component analysis. ICGST Int. J. Graph. Vis. Image Process. GVIP 9:11-17. Cespedes, I., J. Ophir, H. Ponnekanti, and N. Maklad. 1993. Elastography: elasticity imaging using ultrasound with application to muscle and breast in vivo. Ultrasonic imaging 15(2):73-88. Chang, C.-C., and C.-J. Lin. 2011. LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3):1-27. Heimann, T., Meinzer, H.-P. 2009. Statistical shape models for 3D medical image segmentation: A review. Medical Image Analysis 13(4):543-563. Kass M. , W. A., and Terzopoulos D. . 1988. Snakes: active contour models. International Journal of Computer Vision 1(4):p.321~331. Madjar, H., and E. B. Mendelson. 2008. The practice of breast ultrasound: techniques, findings, differential diagnosis. Thieme. Ophir, J., I. Cespedes, H. Ponnekanti, Y. Yazdi, and X. Li. 1991. Elastography: a quantitative method for imaging the elasticity of biological tissues. Ultrasonic imaging 13(2):111-134. Ophir, J., B. Garra, F. Kallel, E. Konofagou, R. Righetti, and T. Varghese. 2000. Elastographic Imaging. Ultrasound in Med. Biol 26(1):s23-s29. Saslow, D., J. Hannan, J. Osuch, M. H. Alciati, C. Baines, M. Barton, J. K. Bobo, C. Coleman, M. Dolan, and G. Gaumer. 2004. Clinical breast examination: practical recommendations for optimizing performance and reporting. CA: A Cancer Journal for Clinicians 54(6):327-344. Sergios Theodoridis, Aggelos Pikrakis, Konstantinos Koutroumbas, and D. Cavouras. 2010. An Introduction to Pattern Recognition: A MATLAB Approach. ACADEMIC PRESS. Wellman, P., R. D. Howe, E. Dalton, and K. A. Kern. 1999. Breast tissue stiffness in compression is correlated to histological diagnosis. Harvard BioRobotics Laboratory Technical Report. 馬偕紀念醫院. 2013. 乳癌診療之原則與新趨勢. 台灣: 馬偕醫院. Available at: http://www.mmh.org.tw/taitam/gen_su/edu_breast.asp. 黃哲勳. 2012. 乳房彈性超音波在乳癌診斷的應用. Available at: http://cms03p.vghks.gov.tw/periodical/pdf/101/1507/101150705.pdf. 簡禎富, and 許嘉裕. 2014. 資料挖礦與大數據分析. 前程文化, 台灣. Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm 范睿豪, 2012. 三維乳房腫瘤外形主成分分析應用於乳房腫瘤橫向探測實驗. 碩士論文.台灣大學生物產業機電工程學系. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52579 | - |
dc.description.abstract | 乳癌為目前全球女性發生率最高的癌症,早期的檢測可增加乳癌的治癒率。乳房超音波影像為常用來進行診斷的方法之一,為了提升準確度,本研究團隊設計一個乳房超音波的輔助診斷系統,在得到影像資訊的同時,亦提供使用者腫瘤的生物力學特性。 系統中應用不同乳房組織硬度不同的特性,此現象常被用於觸診檢查之中。系統中探討探頭與腫瘤之間的力量關係,以主成分分析方法自力量中萃取特徵,作為支持向量回歸模型的輸入,建立腫瘤硬度比預測模型。 本研究中模型與過去模型的差異,在於對腫瘤外形的描述方法與建立預測模型方法,改善了過去模型在內插硬度比以及不規則腫瘤形狀預測不良的問題。在相同條件下,內插硬度比預測誤差降低了14%。而在改變腫瘤形狀描述方法後,對於不規則形狀的預測誤差亦降低了14%。相較於過去的模型,新的模型預測效果較佳,且更趨近於臨床的應用。 | zh_TW |
dc.description.abstract | The stiffness of different breast tissues are different. And this phenomenon is often used in clinical palpation. But the result of palpation is subjective. Thus there are increasing researches aim for providing the physicians secondary opinions. And some study is related to the tumor biomechanical properties. In previous research, we used the force relation between probe and tumor. And extract some features from the force curves. Then we construct a neural network biomechanical model to predict tumor hardness ratio. However, the hardness prediction of the irregular shape tumor and the internal hardness tumor samples are bad. In this thesis, the problems of previous model are improved. I construct a support vector regression biomechanical model, and use the tumor shape statistic model to express the tumor appearance. Then the relative error of internal hardness prediction decrease 14%, and the error of irregular shape tumor hardness prediction also decrease 14%. Compared to previous model, the new model is closer to clinical application. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T16:19:14Z (GMT). No. of bitstreams: 1 ntu-104-R01631019-1.pdf: 5481174 bytes, checksum: d55a6ea89d49b43f96fde0dac9579a3e (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 口試委員會審定書 i 致謝 ii 摘要 iii Abstract iv 目錄 v 圖目錄 vii 表目錄 x 第一章 緒論 1 1.1 研究背景 1 1.2 研究目的 4 1.3 文獻探討 4 1.3.1 超音波彈性影像 4 1.3.2 力量探測實驗 7 1.4 問題描述 8 1.4.1 內插硬度比預測問題 8 1.4.2 不規則形狀腫瘤預測問題 9 第二章 研究方法 12 2.1 研究架構 12 2.2 主成分分析方法 13 2.3 支持向量回歸(Support Vector Regression, SVR) 15 第三章 腫瘤硬度預測模型 18 3.1 硬度預測模型建立流程 18 3.2 仿真乳房模型建立 19 3.2.1 仿體規劃 19 3.2.2 製作方法 24 3.2.2.1 材料選擇 24 3.2.2.2 模具製作 25 3.3 力量探測實驗 27 3.4 硬度預測模型建立 30 3.4.1 資料預處理 30 3.4.2 特徵萃取 33 3.4.3 回歸模型建立 39 第四章 結果與討論 43 4.1 不規則形狀SVR模型 43 4.2 ANN與SVR規則形狀模型比較 45 4.3 不規則形狀腫瘤預測效果比較 46 4.3.1 腫瘤形狀近似方法 46 4.3.2 突顯腫瘤力量回饋的曲線預處理流程 49 4.3.3 討論規則與不規則腫瘤形狀力量差異 52 4.3.4 腫瘤形狀與力量關係 56 第五章 結論與未來展望 57 參考文獻 58 | |
dc.language.iso | zh-TW | |
dc.title | 乳房腫瘤之形狀力學模型建立 | zh_TW |
dc.title | Construction of Breast Tumor Shape-Biomechanical Model | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蕭俊祥(Jin-Siang Shaw),陳達人(Dar-Ren Chen),陳倩瑜(Chien-Yu Chen) | |
dc.subject.keyword | 乳房腫瘤,支持向量回歸,形狀統計學模型,主成分分析,生物力學特性, | zh_TW |
dc.subject.keyword | Breast Tumor,Support Vector Regression,Statistic Shape Model,Principal Component Analysis,Biomechanics Property, | en |
dc.relation.page | 59 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-08-17 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
顯示於系所單位: | 生物機電工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-104-1.pdf 目前未授權公開取用 | 5.35 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。