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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51786完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳永耀(Yung-Yaw Chen) | |
| dc.contributor.author | Wei-Ju Hsu | en |
| dc.contributor.author | 許瑋如 | zh_TW |
| dc.date.accessioned | 2021-06-15T13:49:43Z | - |
| dc.date.available | 2020-12-01 | |
| dc.date.copyright | 2015-12-01 | |
| dc.date.issued | 2015 | |
| dc.date.submitted | 2015-10-21 | |
| dc.identifier.citation | [1] T. Lange, S. Eulenstein, M. Hünerbein, and P.-M. Schlag, 'Vessel-based non-rigid registration of MR/CT and 3D ultrasound for navigation in liver surgery,' Computer Aided Surgery, vol. 8, pp. 228-240, 2003.
[2] P. Dumpuri, L. W. Clements, B. M. Dawant, and M. I. Miga, 'Model-updated image-guided liver surgery: preliminary results using surface characterization,' Progress in biophysics and molecular biology, vol. 103, pp. 197-207, 2010. [3] S. Suwelack, S. Röhl, S. Bodenstedt, D. Reichard, R. Dillmann, T. dos Santos, et al., 'Physics-based shape matching for intraoperative image guidance,' Medical physics, vol. 41, p. 111901, 2014. [4] D. Lee, W. H. Nam, J. Y. Lee, and J. B. Ra, 'Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information,' Physics in medicine and biology, vol. 56, p. 117, 2011. [5] P. A. Yushkevich, J. Piven, H. C. Hazlett, R. G. Smith, S. Ho, J. C. Gee, et al., 'User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability,' Neuroimage, vol. 31, pp. 1116-1128, 2006. [6] S. Pieper, M. Halle, and R. Kikinis, '3D Slicer,' in Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, 2004, pp. 632-635. [7] Hibbitt, Karlsson, and Sorensen, ABAQUS/standard user's Manual vol. 1: Hibbitt, Karlsson & Sorensen, 2001. [8] T. Lange, N. Papenberg, S. Heldmann, J. Modersitzki, B. Fischer, H. Lamecker, et al., '3D ultrasound-CT registration of the liver using combined landmark-intensity information,' International journal of computer assisted radiology and surgery, vol. 4, pp. 79-88, 2009. [9] G. P. Penney, J. M. Blackall, M. Hamady, T. Sabharwal, A. Adam, and D. J. Hawkes, 'Registration of freehand 3D ultrasound and magnetic resonance liver images,' Medical image analysis, vol. 8, pp. 81-91, 2004. [10] W. Wein, S. Brunke, A. Khamene, M. R. Callstrom, and N. Navab, 'Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention,' Medical image analysis, vol. 12, pp. 577-585, 2008. [11] I. Bitter, A. E. Kaufman, and M. Sato, 'Penalized-distance volumetric skeleton algorithm,' Visualization and Computer Graphics, IEEE Transactions on, vol. 7, pp. 195-206, 2001. [12] T. Rohlfing, C. R. Maurer Jr, W. G. O’Dell, and J. Zhong, 'Modeling liver motion and deformation during the respiratory cycle using intensity-based nonrigid registration of gated MR images,' Medical physics, vol. 31, pp. 427-432, 2004. [13] D. L. Hill, P. G. Batchelor, M. Holden, and D. J. Hawkes, 'Medical image registration,' Physics in medicine and biology, vol. 46, p. R1, 2001. [14] U. Meier, O. López, C. Monserrat, M. C. Juan, and M. Alcaniz, 'Real-time deformable models for surgery simulation: a survey,' Computer methods and programs in biomedicine, vol. 77, pp. 183-197, 2005. [15] P. J. Besl and N. D. McKay, 'Method for registration of 3-D shapes,' in Robotics-DL tentative, pp. 586-606, 1992. [16] L. W. Clements, W. C. Chapman, B. M. Dawant, R. L. Galloway Jr, and M. I. Miga, 'Robust surface registration using salient anatomical features for image-guided liver surgery: algorithm and validation,' Medical physics, vol. 35, pp. 2528-2540, 2008. [17] J. Ou, R. Ong, T. Yankeelov, and M. Miga, 'Evaluation of 3D modality-independent elastography for breast imaging: a simulation study,' Physics in medicine and biology, vol. 53, p. 147, 2008. [18] T. S. Pheiffer, R. C. Thompson, D. C. Rucker, A. L. Simpson, and M. I. Miga, 'Model-based correction of tissue compression for tracked ultrasound in soft tissue image-guided surgery,' Ultrasound in medicine & biology, vol. 40, pp. 788-803, 2014. [19] L. Jerábková, 'Interactive cutting of finite elements based deformable objects in virtual environments,' RWTH Aachen University, 2007. [20] A. M. Britto, 'Running ABAQUS 6.4,' 2005. [21] V. Caselles, R. Kimmel, and G. Sapiro, 'Geodesic active contours,' International journal of computer vision, vol. 22, pp. 61-79, 1997. [22] W. E. Lorensen and H. E. Cline, 'Marching cubes: A high resolution 3D surface construction algorithm,' in ACM siggraph computer graphics, 1987, pp. 163-169. [23] P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, and G. Ranzuglia, 'MeshLab: an Open-Source Mesh Processing Tool,' in Eurographics Italian Chapter Conference, pp. 129-136, 2008. [24] F. J. Carter, T. G. Frank, P. J. Davies, D. McLean, and A. Cuschieri, 'Measurements and modelling of the compliance of human and porcine organs,' Medical Image Analysis, vol. 5, pp. 231-236, 2001. [25] A. Nava, E. Mazza, M. Furrer, P. Villiger, and W. Reinhart, 'In vivo mechanical characterization of human liver,' Medical image analysis, vol. 12, pp. 203-216, 2008. [26] M. P. Ottensmeyer, A. E. Kerdok, R. D. Howe, and S. L. Dawson, 'The effects of testing environment on the viscoelastic properties of soft tissues,' in Medical Simulation, ed: Springer, pp. 9-18, 2004. [27] B. K. Tay, J. Kim, and M. A. Srinivasan, 'In vivo mechanical behavior of intra-abdominal organs,' IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING BME, vol. 53, p. 2129, 2006. [28] D. Valtorta and E. Mazza, 'Dynamic measurement of soft tissue viscoelastic properties with a torsional resonator device,' Medical Image Analysis, vol. 9, pp. 481-490, 2005. [29] M. Kauer, V. Vuskovic, J. Dual, G. Székely, and M. Bajka, 'Inverse finite element characterization of soft tissues,' Medical Image Analysis, vol. 6, pp. 275-287, 2002. [30] I. Peterlík, C. Duriez, and S. Cotin, 'Modeling and real-time simulation of a vascularized liver tissue,' in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012, ed: Springer, pp. 50-57, 2012. [31] S. Umale, S. Chatelin, N. Bourdet, C. Deck, M. Diana, P. Dhumane, et al., 'Experimental in vitro mechanical characterization of porcine Glisson's capsule and hepatic veins,' Journal of biomechanics, vol. 44, pp. 1678-1683, 2011. [32] H. Yamada and F. G. Evans, 'Strength of biological materials,' 1970. [33] A. K. Siriwardena, J. M. Mason, S. Mullamitha, H. C. Hancock, and S. Jegatheeswaran, 'Management of colorectal cancer presenting with synchronous liver metastases,' Nature Reviews Clinical Oncology, vol. 11, pp. 446-459, 2014. [34] D. M. Cash, M. Miga, T. K. Sinha, R. L. Galloway, and W. C. Chapman, 'Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements,' Medical Imaging, IEEE Transactions on, vol. 24, pp. 1479-1491, 2005. [35] L. W. Clements, 'Salient anatomical features for robust surface registration and atlas-based model updating in image-guided liver surgery,' Vanderbilt University, 2009. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51786 | - |
| dc.description.abstract | 在微創手術中,知道在肝臟切割手術中肝臟內部血管及腫瘤位置是困難的,醫師只能憑藉術前的電腦斷層掃瞄影像當作導引大約知道肝臟中血管及腫瘤分佈位置,但肝臟會因為不同的手術操作而產生形變,使得術前的資料產生變動。藉由血管位置計算的幫助,醫師可以更直覺的操作手術且可以降低可能切割到大的肝臟血管(>3mm)或腫瘤的風險。
在本論文中,使用的是從電腦斷層掃瞄影像所建立的有限元素法模型去模擬形變,藉由分析已形變(手術中)及未形變(手術前)肝臟表面差異得到位移邊界條件並用來模擬肝臟形變,在有限元素模擬之後,可以得到形變後(手術中)的血管及腫瘤分布位置。我們利用模擬資料以及體外豬肝實驗去驗證演算法,在模擬實驗中,平均肝臟表面的誤差在0.35mm,平均內部的誤差在0.28mm,在體外豬肝實驗中,平均肝臟表面誤差在0.86mm,平均內部誤差在2.26mm。 | zh_TW |
| dc.description.abstract | In minimally invasive surgery, knowing the position of internal structures of tissue such as vessels and tumors is a challenge. Surgeons only depend on preoperative CT images to know positions of vessels and tumors, but liver is deformed by different surgical procedures. The preoperative information is no longer precise. With the help of vessel-tracking system, surgeons can operate the surgical tasks more intuitively and decrease the risk from cutting large vessels and tumors.
In this thesis, finite element model built from preoperative CT is used to calculate deformations. The difference between intraoperative and preoperative surface data is used as displacement boundary conditions applied to simulate the deformations. After finite element computation, the intraoperative positions of vessels and tumors are obtained. The proposed algorithms are first validated through simulation data based on surgical scenario in minimally invasive surgery, then validated through ex vivo porcine liver experiment data. The mean error of liver surface is 0.35mm and mean error of internal structure is 0.28mm in simulation. The mean error of liver surface is 0.86mm and mean error of internal structures is 2.26mm in ex vivo porcine liver experiment. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T13:49:43Z (GMT). No. of bitstreams: 1 ntu-104-R02921060-1.pdf: 4881131 bytes, checksum: 6ef8832fef6fb884f63ac8174ed5b226 (MD5) Previous issue date: 2015 | en |
| dc.description.tableofcontents | 誌謝....................................................................i
中文摘要...............................................................ii ABSTRACT..............................................................iii CONTENTS...............................................................iv LIST OF FIGURES........................................................vi LIST OF TABLES.......................................................xiii Chapter 1 Introduction............................................1 1.1 Motivation and Problem Definition...............................2 1.2 Previous Work of Computation on Non-rigid Tissue Deformation....4 1.3 Proposed Approach...............................................7 1.4 Thesis Overview.................................................9 Chapter 2 Computation on Non-rigid Tissue Deformation............10 2.1 Deformation Compensation for Non-Rigid Tissue..................13 2.1.1 Geometrical Method.............................................13 2.1.2 Physical Method................................................21 2.2 Comparisons and Summary........................................28 2.3 Finite Element Analysis........................................30 2.3.1 Principle of Finite Element Method.............................30 2.3.2 Finite Element Simulation on Abaqus............................34 Chapter 3 Finite Element Model-Based Vessel Tracking Approach....44 3.1 System Overview................................................45 3.2 Model Construction.............................................47 3.2.1 Image Segmentation.............................................47 3.2.2 Three Dimensional FEM Model....................................54 3.2.3 Modeling Technique of Composite Property of Liver with Vessels.58 3.3 Registration Method............................................61 3.4 Deformation Computation........................................65 3.4.1 Boundary Condition Analysis....................................65 3.4.2 Iteratively Optimization Process...............................67 Chapter 4 Validation by Simulations..............................69 4.1 Registration Method............................................70 4.2 Deformation Computation........................................76 4.3 Discussions....................................................79 Chapter 5 Liver Deformation Experiment...........................80 5.1 Experiment Setup...............................................81 5.2 Results of Deformation Experiment..............................90 5.3 Discussions...................................................100 5.4 Comparison....................................................101 Chapter 6 Conclusions and Future Work...........................107 REFERENCES............................................................109 | |
| dc.language.iso | en | |
| dc.subject | 非剛體對位 | zh_TW |
| dc.subject | 有限元素分析法 | zh_TW |
| dc.subject | 影像導引手術 | zh_TW |
| dc.subject | 肝臟切除 | zh_TW |
| dc.subject | 形變模型 | zh_TW |
| dc.subject | non-rigid registration | en |
| dc.subject | finite element analysis | en |
| dc.subject | image-guided surgery | en |
| dc.subject | liver resection | en |
| dc.subject | deformable model | en |
| dc.title | 基於有限元素法模型模擬肝臟形變並應用於血管定位 | zh_TW |
| dc.title | Finite Element Model-Based Simulation of Liver
Deformation for Vessel Tracking | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林文澧(Wen-Li Lin),顏家鈺(Jia-Yush Yen),何明志(Ming-Chih Ho) | |
| dc.subject.keyword | 有限元素分析法,影像導引手術,肝臟切除,形變模型,非剛體對位, | zh_TW |
| dc.subject.keyword | finite element analysis,image-guided surgery,liver resection,deformable model,non-rigid registration, | en |
| dc.relation.page | 111 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2015-10-22 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位: | 電機工程學系 | |
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