請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/35371
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 李學智 | |
dc.contributor.author | Geng-Shi Jeng | en |
dc.contributor.author | 鄭耿璽 | zh_TW |
dc.date.accessioned | 2021-06-13T06:49:59Z | - |
dc.date.available | 2006-01-01 | |
dc.date.copyright | 2005-08-01 | |
dc.date.issued | 2005 | |
dc.date.submitted | 2005-07-28 | |
dc.identifier.citation | [1] J. A. Jensen, Estimation of blood velocities using ultrasound: a signal processing approach. New York: Cambridge Univ. Press, 1996.
[2] K. W. Ferrara and G. DeAngelis, “Color flow mapping,” Ultrasound Med. Biol., vol. 23, pp. 321–345, 1997. [3] C. Kasai, K. Namekawa, A. Koyano, and R. Omoto, “Real-time two-dimensional blood flow imaging using an autocorrelation technique,” IEEE Trans. Son. Ultrason., vol. SU–32, pp. 458–464, 1985. [4] T. Loupas, J. T. Powers, and R. W. Gill, “An axial velocity estimator for ultrasound blood flow imaging, based on a full evaluation of the Doppler equation by means of a two-dimensional autocorrelation approach,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 42, no. 4, pp. 672–688, 1995. [5] K. W. Ferrara and V. R. Algazi, “A new wideband spread target maximum likelihood estimator for blood velocity estimation - Part I: Theory,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 38, no. 1, pp. 1–16, 1991. [6] S. K. Alam and K. J. Parker, “The butterfly search technique for estimation of blood velocity,” Ultrasound Med. Biol., vol. 21, no. 5, pp. 657–670, 1995. [7] 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. [8] 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. Mag. vol. 15, pp. 60–71, 1996. [9] D. A. Knapik, B. Starkoski, C. J. Pavlin, and F. S. Foster, “A 100–200 MHz ultrasound biomicroscope,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 47, no. 6, pp. 1540–1549, 2000. [10] K. W. Ferrara, B. G. Zagar, J. B. Sokil-Melgar, R. H. Silverman, and I. M. Aslanidis, “Estimation of blood velocity with high frequency ultrasound,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 43, no. 1, pp. 149–157, 1996. [11] C. J. Pavlin, D. A. Christopher, P. N. Burns, and F. S. Foster, “High frequency Doppler ultrasound examination of blood flow in the anterior segment of the eye,” Am. J. Ophthalmol., vol. 126, no. 4, pp. 597–600, 1998. [12] D. A. Christopher, P. N. Burns, and F. S. Foster, “High frequency continuous wave Doppler ultrasound system for the detection of blood flow in the microcirculation,” Ultrasound Med. Biol., vol. 22, no. 3, pp. 1196–1203, 1996. [13] D. A. Christopher, P. N. Burns, B. G. Starkoski, and F. S. Foster, “A high- frequency pulsed wave Doppler ultrasound system for the detection and imaging of blood flow in the microcirculation,” Ultrasound Med. Biol., vol. 23, no. 7, pp. 997–1015, 1997. [14] D. E. Kruse, R. H. Silverman, R. J. Fornaris, D. J. Coleman, and K. W. Ferrara, “A swept-scanning mode for estimation of blood velocity in the microvasculature,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 6, pp. 1437–1440, 1998. [15] D. E. Goertz, D. A. Christopher, J. L. Yu, R. S. Kerbel, P. N. Burns, and F. S. Foster, “High-frequency color flow imaging of the microcirculation,” Ultrasound Med. Biol., vol. 26, no. 1, pp. 63–71, 2000. [16] D. E. Goertz, J. L. Yu, R. S. Kerbel, P. N. Burns, and F. S. Foster, “High-frequency 3-D color-flow imaging of the microcirculation,” Ultrasound Med. Biol., vol. 29, no. 1, pp. 39–51, 2003. [17] F. S. Foster, P. N. Burns, D. H. Simpson, S. R. Wilson, D. A. Christopher, and D. E. Goertz, “Ultrasound for the visualization and quantification of tumor microcirculation,” Cancer Metastasis Rev., vol. 19, pp. 131–138, 2000. [18] C. Kargel, G. Plevnik, B. Trummer, and M. F. Insana, “Doppler ultrasound systems designed for tumor blood flow imaging,” IEEE Trans. Ins. and Meas., vol. 53, no. 2, pp. 524–536, 2004. [19] M.-L. Li, Y.-F Chen, W.-J. Guan, and P.-C. Li, “A Digital Ultrasonic System for Small Animal Imaging,” Ultrason. Imag., vol. 26, pp. 85–99, 2004. [20] P.-C. Li, Y.-F Chen, W.-J. Guan, “Ultrasonic high frequency blood flow imaging of small animal tumor models,” in Proc. IEEE Ultrason. Symp., 2003, pp. 1598–1601. [21] C. K. Phoon, O. Aristizábal, and D. H. Turnbull, “40 MHz Doppler characterization of umbilical and dorsal aortic blood flow in the early mouse embryo,” Ultrasound Med. Biol., vol. 26, no. 8, pp. 1275–1283, 2000. [22] F. S. Foster et al., “A new ultrasound instrument for in vivo microimaging of mice,” Ultrasound Med. Biol., vol. 28, no. 9, pp. 1165–1172, 2002. [23] S. M. Day, J. L. Reeve, D. D. Myers, and W. P. Fay, “Murine Thrombosis Models,” Thromb Haemost, vol. 92, pp. 486–494, 2004. [24] A. Liu, A.L. Joyner and D.H. Turnbull, “Alteration of limb and brain patterning in early mouse embryos by ultrasound-guided injection of Shh-expressing cells,” Mech Dev, vol. 75, pp. 107–115, 1998. [25] C.-K. Yeh, K. W. Ferrara, and D. E. Kruse, “High-resolution functional vascular assessment with ultrasound,” IEEE Trans. Med. Imag., vol. 23, no. 10, pp. 1263–1274, 2004. [26] R. V. Shohet et al., “Echocardiographic destruction of albumin microbubbles directs gene delivery to the myocardium,” Circulation, vol. 101, pp. 2554–2556, 2000. [27] D. E. Kruse and K. W. Ferrara, “A new high resolution color flow system using an eigendecomposition-based adaptive filter for clutter rejection,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 49, no. 12, pp. 1739–1754, 2002. [28] H. Torp, “Clutter rejection filters in color flow imaging: a theoretical approach,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 44, no. 2, pp. 417–424, 1997. [29] A. Bjaerum, H. Torp, and K. Kristofferson, “Clutter filters design for ultrasound color flow imaging,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 49, no. 2, pp. 204–216, 2002. [30] P.-C. Li, C.-J. Cheng, and C.-K. Yeh, “On velocity estimation using speckle decorrelation,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 48, no. 4, pp. 1084–1091, 2001. [31] J. R. Overbeck, K. W. Beach, and D. E. Strandness, Jr., “Vector Doppler: Accurate measurement of blood velocity in two dimensions,” Ultrasound Med. Biol., vol. 18, pp. 19–31, 1992. [32] M. D. Fox and W. D. Gardiner, “Three-dimensional Doppler velocimetry of flow jets,” IEEE Trans. Biomed. Eng., vol. 35, no. 10, pp. 834–841, 1988. [33] M. E. Anderson, “Multi-dimensional velocity estimation with ultrasound using spatial quadrature,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 3, pp. 852–861, 1998. [34] J. A. Jensen and P. Munk, “A new method for estimation of velocity vectors,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 3, pp. 837–851, 1998. [35] G. E. Trahey, J. W. Allison, and O. T. von Ramm, “Angle independent ultrasonic detection of blood flow, “ IEEE Trans. Biomed. Eng., vol. 34, no. 12, pp. 965–967, 1987. [36] L. N. Bohs, B. H. Friemel, and G. E. Trahey, “Experimental velocity profiles and volumetric flow via two-dimensional speckle tracking,” Ultrasound Med. Biol., vol. 21, pp. 885–898, 1995. [37] L. N. Bohs, B. J. Geiman, M. E. Anderson, S. M. Breit,and G. E. Trahey, “Ensemble tracking for 2D vector velocity measurement: experimental and initial clinical results,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 4, pp. 912–923, 1998. [38] V. L. Newhouse, E. S. Furgason, G. F. Johnson, and D. A. Wolf, “The dependence of ultrasound bandwidth on beam geometry,” IEEE Trans. Sonics Ultrason., vol.27, no. 2, pp. 50–59, 1980. [39] V. L. Newhouse, D. Censor, T. Vontz, J. A. Cisneros, and B. B. Goldberg, “Ultrasound Doppler probing of flows transverse with respect to beam axis,” IEEE Trans. Biomed. Eng., vol. 34, no. 10, pp. 779–789, 1987. [40] P.-C. Li, C.-J. Cheng, and C.-C. Shen, “Doppler angle estimation using correlation,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 47, no. 1, pp. 188–196, 2000. [41] C.-K. Yeh and P.-C. Li, “Doppler angle estimation using AR modeling,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 49, no. 6, pp. 683–692, 2002. [42] B.-R Lee, H. K. Chiang, C.-D. Kuo, W.-L. Lin, and S.-K. Lee, “Doppler angle and flow velocity estimations using the classic and transverse Doppler effects,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 46, no. 1, pp. 252–256, 1999. [43] M. O’Donnell, A. R. Skovoroda, B. M. Shapo, and S. Y. Elemlianov, “Internal displacement and strain imaging using ultrasonic speckle tracking,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 41, no. 3, pp. 314–325, 1994. [44] P.-C. Li, C.-Y. Li, and W.-C. Yeh, “Tissue motion and elevational speckle decorrelation in freehand 3D ultrasound,” Ultrason. Imag., vol. 24, pp. 1–12, 2002. [45] W. F. Walker and G. E. Trahey, “The application of k-space in pulse echo ultrasound,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 3, pp. 541–558, 1998. [46] B. H. Friemel, L. N. Bohs, K. R. Nightingale, and G. E. Trahey, “Speckle decorrelation due to two-dimensional flow gradients,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 2, pp. 317–327, 1998. [47] M.-L. Li, Wei-Jung Guan, and P.-C. Li, “Improved synthetic aperture focusing with applications in high-frequency ultrasound imaging,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 51, no. 1, pp. 63–70, 2004. [48] C. Passmann and H. Ermert, “A 100-MHz ultrasound imaging system for dermatologic and ophthalmologic diagnostics,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 43, no. 4, pp. 545–552, 1996. [49] P.-C. Li and M.-L. Li, “Adaptive imaging using the generalized coherence factor,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 50, no. 2, pp. 128–141, 2003. [50] J. A. Jensen, “ Field: A program for simulating ultrasound systems,” Med. Biol. Eng. Comp., 10th Nordic-Baltic Conference on Biomedical Imaging, vol. SU–4, Part 1, pp. 351–353, 1996b. [51] W. T. Mayo and P. M. Embree, “Two-dimensional processing of pulsed Doppler signals,” U.S. Patent 4930513, Jun 5, 1990. [52] L. S. Wilson, “Description of broad-band pulsed Doppler ultrasound processing using the two-dimensional Fourier transform.” Ultrason. Imag., vol. 13, pp. 301–315, 1991. [53] P. J. Vaitkus and R. S. C. Cobbold, “A new time-domain narrowband velocity estimation technique for Doppler ultrasound flow imaging. I. Theory,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 45, no. 3, pp. 939–954, 1998. [54] P. Tortoli, G. Guidi, and V. L. Newhouse, “Improved blood velocity estimation using the maximum Doppler frequency,” Ultrasound Med. Biol., vol. 21, pp. 527–532, 1995. [55] A. H. Steinman, J. Tavakkoli, J. G. Myers, R. S. C. Cobbold, and K.W. Johnston, “Sources of error in maximum velocity estimation using linear phased-array Doppler systems with steady flow,” Ultrasound Med. Biol., vol. 27, pp. 655–664, 2001. [56] M. O’Donnell, “Coded excitation system for improving the penetration of real-time phased-array imaging systems,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 39, no. 3, pp. 341–351, 1992. [57] J. M. Borsboom, C. T. Chin, A. Bouakaz, M. Versluis, and N. de Jong, “Harmonic chirp imaging method for ultrasound contrast agent,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 52, no. 2, pp. 241–249, 2005. [58] D. H. Simpson, T. C. Chien, and P. N. Burn, “Pulse inversion Doppler: a new method for detecting nonlinear echoes from microbubble contrast agents,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 46, no. 2, pp. 372–382, 1999. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/35371 | - |
dc.description.abstract | 頻率大於20MHz的高頻超音波影像系統能夠觀察細微的組織以及量測微弱血流速度,然而由於高頻陣列探頭製作技術的困難,目前高頻系統大都採用單一探頭、機械掃瞄的方式來取得影像資訊,掃瞄的方法主要採用離散步進的方式(step scan),這種方法相當耗時,無法提供即時的血流資訊。另一種稱作掃掠式掃瞄的技術(swept scan)則是讓探頭連續不間斷地移動,因此能大幅縮短成像的時間。雖然掃掠式掃瞄已應用於目前的高頻系統,然而探頭的連續移動對於流速的估計有著不可忽略的影響。為此,本論文主要目的則是從理論面以及實驗探討掃掠式掃瞄對於流速估計的效應,並針對掃掠式高頻系統提出一個新的定量流速估計方法。
本文首先利用二維空間頻譜的概念(稱為k-space)來量化掃掠式掃瞄對於二維流速估測的影響。我們證明了移動物體的空間頻譜等效於其時間頻譜 (亦即,由都卜勒頻率以及RF頻率所構成的二維頻譜)。另外,相較於離散式掃瞄,掃掠式掃瞄則會造成都卜勒頻寬的變動,此頻寬變動導致流速估計的偏差及變異。為了校正此一速度偏差並提高估計的精確度,我們提出一個基於k-space的流速向量估計方法。我們利用模擬以及體外流體實驗來驗證所提出的新方法,此外,我們亦利用45MHz的高頻系統來測量老鼠尾巴內的靜脈流速,實驗結果顯示所提出的流速向量估計方法適用於掃掠式高頻系統,並能有效地降低流速以及血管角度估計的誤差。 本研究之主要貢獻,在於以k-space之方式建構超音波血流分析之理論架構,並完整分析掃掠式掃描對於流速計算之影響,提升超音波小動物影像中定量血流分析之能力。 | zh_TW |
dc.description.abstract | The rapid developments in high-frequency ultrasound systems (operating at higher than 20 MHz) have allowed visualization of fine tissue structures and assessment of small vessels with slow flows. Due to the lack of high-frequency arrays, however, most current high-frequency systems use mechanically scanned, single-element transducers that are moved through a series of discrete positions. This scan technique, called the step-scan, is relatively time consuming and cannot provide flow information in real-time. An alternative technique, called the swept-scan, involves continuous scanning a transducer and is capable of improving the data acquisition time. Although the swept-scan technique is currently employed in high-frequency ultrasound systems, the continuous transducer movement may have nonnegligible effects on accuracy of velocity estimation. It is therefore the purpose of this thesis to thoroughly investigate such effects, and to further develop a new quantitative flow estimation method.
In this thesis, a spatial frequency domain (i.e., k-space) approach is employed to quantify the effects of swept scanning on the spectral-broadening-based vector velocity estimation method. It is shown that the k-space representation of a 2-D moving object is equivalent to a Doppler-RF frequency domain representation, and that transducer movement in the swept-scan technique results in a change in Doppler bandwidth. The spectral broadening caused by swept scan introduces velocity estimation bias and variance that are not present in the step-scan technique. In order to correct such effects and improve velocity estimation accuracy, a robust vector velocity estimation method is developed based on the proposed k-space approach. Both simulations and in vitro experiments were performed to evaluate performance of the proposed vector velocity estimator. Furthermore, in vivo measurements of mouse tail vessels were also conducted using a 45-MHz transducer. The results demonstrate that the proposed vector velocity estimator is feasible in swept scan and can effectively reduce the velocity and angle estimation errors. The main contributions of the thesis include development of a theoretical framework for ultrasonic flow analysis using a k-space approach. Based on this framework, effects of the swept scan on flow estimation were thoroughly investigated, thus making quantitative flow analysis in ultrasonic small animal imaging more feasible. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T06:49:59Z (GMT). No. of bitstreams: 1 ntu-94-D87942011-1.pdf: 2643727 bytes, checksum: d0ae04b17e65b242101b813dbf705acc (MD5) Previous issue date: 2005 | en |
dc.description.tableofcontents | 中文摘要 I
ABSTRACT II LIST OF SYMBOLS III TABLE OF CONTENTS V LIST OF FIGURES VII LIST OF TABLES XII CHAPTER 1 INTRODUCTION 1 1.1 DOPPLER ULTRASOUND 1 1.1.1 Phase-shift Estimation Techniques 2 1.1.2 Time-shift Estimation Techniques 4 1.2 HIGH-FREQUENCY FLOW ESTIMATION 4 1.2.1 Mechanical Scanning Techniques 6 1.2.2 Difficulties in High-frequency Flow Estimation 8 1.3 VECTOR VELOCITY ESTIMATION METHODS 9 1.3.1 Multiple Beam Methods 9 1.3.2 Spatial Quadrature Methods 10 1.3.3 Speckle Tracking Methods 11 1.3.4 Spectral-broadening-based Methods 12 1.4 A BRIEF INTRODUCTION TO K-SPACE 13 1.5 DESCRIPTION OF THE EXPERIMENTAL SETUP 15 1.6 SCOPE AND DISSERTATION ORGANIZATION 16 CHAPTER 2 EFFECTS OF SWEPT SCANNING ON VELOCITY ESTIMATION 18 2.1 BASIC PRINCIPLES 18 2.1.1 K-space Representation in a Swept-scan: a Stationary Object 19 2.1.2 K-space Representation in a Swept-scan: 2-D motion 21 2.1.3 Comparison Between Swept and Step Scanning 25 2.2 EFFECTS OF SWEPT-SCANNING ON VECTOR VELOCITY ESTIMATION 27 2.2.1 Velocity Resolution 28 2.2.2 Spectral Aliasing 28 2.2.3 The Presence of Clutter Signals 30 2.3 EXPERIMENTAL INVESTIGATIONS 32 2.3.1 Doppler Spectral Broadening for a Stationary Phantom 32 2.3.2 Performance of Autocorrelation-based Axial Velocity Estimators 34 2.4 CONCLUDING REMARKS 36 CHAPTER 3 K-SPACE VECTOR VELOCITY ESTIMATOR IN SWEPT-SCAN 37 3.1 THEORY 37 3.2 SIMULATION RESULTS 39 3.2.1 Kernel Size 39 3.2.2 Constant Flows 41 3.2.3 Spatial Velocity Gradients 43 3.3 EXPERIMENTAL RESULTS-CONSTANT FLOWS 45 3.4 DISCUSSION AND CONCLUDING REMARKS 49 CHAPTER 4 EXPERIMENTAL RESULTS 52 4.1 IN VITRO RESULTS 52 4.2 IN VIVO RESULTS 55 4.3 DISCUSSION AND CONCLUDING REMARKS 63 CHAPTER 5 DISCUSSION 66 5.1 K-SPACE ESTIMATION IN SWEPT-SCAN VS. SPECTRAL- BROADENING-BASED ESTIMATION IN STEP-SCAN 66 5.2 K-SPACE VECTOR VELOCITY ESTIMATOR USING CODED EXCITATION 70 5.3 APPLYING K-SPACE ESTIMATOR TO ELECTRONIC-SCANNING ARRAY SYSTEMS 73 5.4 POWER DOPPLER IN SWEPT-SCAN 74 CHAPTER 6 CONCLUSIONS AND FUTURE WORKS 76 APPENDIX A APPROXIMATION OF (2.2) 77 REFERENCES 79 | |
dc.language.iso | en | |
dc.title | 運用K-space方法於超音波掃掠式系統之流速向量估測 | zh_TW |
dc.title | Ultrasonic Vector Velocity Estimation in Swept-scan Using a K-space Approach | en |
dc.type | Thesis | |
dc.date.schoolyear | 93-2 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 李百祺 | |
dc.contributor.oralexamcommittee | 王士豪,葉秩光,郭益源 | |
dc.subject.keyword | 超音波影像,都卜勒超音波,高頻超音波,血流估計,流速向量估計,掃掠式掃描,k-space,空間頻率, | zh_TW |
dc.subject.keyword | Ultrasonic imaging,Doppler ultrasound,high frequency ultrasound,blood velocity estimation,velocity vector estimation,swept scan,k-space,spatial frequency, | en |
dc.relation.page | 84 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2005-07-28 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-94-1.pdf 目前未授權公開取用 | 2.58 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。