請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46149
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 李百祺 | |
dc.contributor.author | Yen-Feng Li | en |
dc.contributor.author | 李彥鋒 | zh_TW |
dc.date.accessioned | 2021-06-15T04:55:40Z | - |
dc.date.available | 2012-08-06 | |
dc.date.copyright | 2010-08-06 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-07-29 | |
dc.identifier.citation | [1] K. K. Shung, Diagnostic Ultrasound: Imaging and Blood Flow Measurements, 2006.
[2] T. L. Szabo, Diagnostic Ultrasound Imaging: Inside Out, 2004. [3] ZONARE. Available: http://www.zonare.com/ [4] VeraSonics. Available: http://www.verasonics.com/ [5] M. J. Quinn, Parallel Programming in C with MPI and OpenMP: McGraw-Hill, 2004. [6] S. Che, M. Boyer, J. Meng, D. Tarjan, J. W. Sheaffer, and K. Skadron, 'A performance study of general-purpose applications on graphics processors using CUDA,' Journal of Parallel and Distributed Computing, vol. 68, pp. 1370-1380, 2008. [7] R. Shams, P. Sadeghi, R. Kennedy, and R. Hartley, 'A Survey of Medical Image Registration on Multicore and the GPU,' Signal Processing Magazine, IEEE, vol. 27, pp. 50-60, 2010. [8] R. E. Daigle, 'Ultrasound Imaging system with pixel oriented processing,' United States Patent 2009/0112095 A1, 2006. [9] NVIDIA. Available: http://www.nvidia.com/ [10] NVIDIA, NVIDIA CUDA Programming Guide, 3.0 ed., 2010. [11] C. Li-wen, H. Ke-hsin, and L. Pai-chi, 'Graphics processing unit-based high-frame-rate color doppler ultrasound processing,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 56, pp. 1856-1860, 2009. [12] H.-J. W. H. J. Hewener, C. Günther, H. Fonfara, S. H. Tretbar and R. M. Lemor, 'A highly customizable ultrasound research platform for clinical use with a software architecture for 2d-3d-reconstruction and processing including closed-loop control ' in Proc. IFMBE Med. Phy., Biomed. Eng., 2009, pp. 342-345. [13] W. Plishker, O. Dandekar, S. S. Bhattacharyya, and R. Shekhar, 'Towards systematic exploration of tradeoffs for medical image registration on heterogeneous platforms,' in Proc. IEEE BioCAS, 2008, pp. 53-56. [14] T. Reichl, J. Passenger, O. Acosta, and O. Salvado, 'Ultrasound goes GPU: real-time simulation using CUDA,' Lake Buena Vista, FL, USA, 2009, pp. 726116-10. [15] M. O'Donnell, 'Efficient parallel receive beam forming for phased array imaging using phase rotation [medical US application],' in Proc. IEEE Ultrason. Symp., 1990, pp. 1495-1498 vol.3. [16] D. P. Shattuck, M. D. Weinshenker, S. W. Smith, and O. T. Vonramm, 'Explososcan: a parallel processing technique for high speed ultrasound imaging with linear phased-arrays,' J. Acoust. Soc. Am., vol. 75, pp. 1273-1282, 1984. [17] J. Bercoff, M. Tanter, and M. Fink, 'Supersonic shear imaging: a new technique for soft tissue elasticity mapping,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 51, pp. 396-409, 2004. [18] J.-Y. Lu, '2D and 3D high frame rate imaging with limited diffraction beams,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 44, pp. 839-856, 1997. [19] M. Karaman, L. Pai-Chi, and M. O'Donnell, 'Synthetic aperture imaging for small scale systems,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 42, pp. 429-442, 1995. [20] J.-y. Lu, J. Cheng, and J. Wang, 'High frame rate imaging system for limited diffraction array beam imaging with square-wave aperture weightings,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 53, pp. 1796-1812, 2006. [21] J. Y. Lu and J. F. Greenleaf, 'Ultrasonic nondiffracting transducer for medical imaging,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 37, pp. 438-447, 1990. [22] T. Hergum, T. Bjastad, K. Kristoffersen, and H. Torp, 'Parallel beamforming using synthetic transmit beams,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 54, pp. 271-280, 2007. [23] R. Y. Chiao, L. J. Thomas, and S. D. Silverstein, 'Sparse array imaging with spatially-encoded transmits,' in Proc. IEEE Ultrason. Symp., 1997, pp. 1679-1682 vol.2. [24] J. A. Jensen, S. I. Nikolov, K. L. Gammelmark, and M. H. Pedersen, 'Synthetic aperture ultrasound imaging,' Ultrasonics, vol. 44, pp. e5-e15, 2006. [25] T. X. Misaridis and J. A. Jensen, 'Space-time encoding for high frame rate ultrasound imaging,' Ultrasonics, vol. 40, pp. 593-597, May 2002. [26] J. A. Jensen and S. I. Nikolov, 'Directional synthetic aperture flow imaging,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 51, pp. 1107-18, Sep 2004. [27] S. I. Nikolov and J. A. Jensen, 'Velocity estimation using synthetic aperture imaging,' in Proc. IEEE Ultrason. Symp., 2001, pp. 1409-1412 vol.2. [28] N. Oddershede and J. A. Jensen, 'Effects influencing focusing in synthetic aperture vector flow imaging,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 54, pp. 1811-1825, Sep 2007. [29] S. Nikolov, K. Gammelmark, and J. Jensen, 'Velocity estimation using recursive ultrasound imaging and spatially encoded signals,' in Proc. IEEE Ultrason. Symp., 2000, pp. 1473-1477 vol.2. [30] S. I. Nikolov and J. A. Jensen, 'In-vivo synthetic aperture flow imaging in medical ultrasound,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 50, pp. 848-856, 2003. [31] S. Nikolov, K. Gammelmark, and J. A. Jensen, 'Recursive ultrasound imaging,' in Proc. IEEE Ultrason. Symp., 1999, pp. 1621-1625. [32] J. Y. Lu, H. Zou, and J. F. Greenleaf, 'Biomedical ultrasound beam forming,' Ultrasound Med. Biol., vol. 20, pp. 403-28, 1994. [33] D. H. Johnson and D. E. Dudgeon, Array signal processing : concepts and techniques. Englewood Cliffs, NJ: Prentice Hall, 1993. [34] J. F. Synnevag, A. Austeng, and S. Holm, 'Adaptive beamforming applied to medical ultrasound imaging,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 54, pp. 1606-1613, Aug 2007. [35] P.-C. Li and M.-L. Li, 'Adaptive imaging using the generalized coherence factor,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 50, pp. 128-141, 2003. [36] S.-L. Wang, C.-H. Chang, H.-C. Yang, Y.-H. Chou, and P.-C. Li, 'Performance Evaluation of Coherence-Based Adaptive Imaging Using Clinical Breast Data,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 54, pp. 1669-1679, 2007. [37] C. H. Frazier and W. D. O'Brien, Jr., 'Synthetic aperture techniques with a virtual source element,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 45, pp. 196-207, 1998. [38] S. Nikolov and J. A. Jensen, 'Virtual ultrasound sources in high-resolution ultrasound imaging,' in Proc. SPIE Med. Imag., 2002, pp. 395-405. [39] K. L. Gammelmark and J. A. Jensen, 'Multielement synthetic transmit aperture imaging using temporal encoding,' IEEE Trans. Med. Imag., vol. 22, pp. 552-563, 2003. [40] K.-S. Kim and T.-K. Song, 'High-frame-rate and high-resolution ultrasound imaging with virtual source element in B-mode ultrasound system based on sparse synthetic transmit aperture method,' in Proc. SPIE Med. Imag., San Diego, CA, USA, 2004, pp. 290-299. [41] B. Moo-Ho and J. Mok-Kun, 'A study of synthetic-aperture imaging with virtual source elements in B-mode ultrasound imaging systems,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 47, pp. 1510-1519, 2000. [42] S. Bjaerum, H. Torp, and K. Kristoffersen, 'Clutter filter design for ultrasound color flow imaging,' IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 49, pp. 204-216, 2002. [43] J. A. Jensen, Estimation of blood velocities using ultrasound : a signal processing approach. Cambridge ; New York, USA: Cambridge University Press, 1996. [44] G. E. Trahey, J. W. Allison, and O. T. von Ramm, 'Angle independent ultrasonic detection of blood flow,' IEEE Trans. Biomed. Eng., vol. 34, pp. 965-7, Dec 1987. [45] 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. 885-98, 1995. [46] H. S. Bilge, M. Karaman, and M. O'Donnell, 'Motion estimation using common spatial frequencies in synthetic aperture imaging,' in Ultrasonics Symposium, 1996. Proceedings., 1996 IEEE, 1996, pp. 1551-1554 vol.2. [47] F. Gran, S. I. Nikolov, and J. A. Jensen, 'Blood velocity estimation using spatio-temporal encoding based on a frequency division approach,' in Proc. IEEE Ultrason. Symp., 2005, pp. 1344-1347. [48] J. A. Jensen, H. Andresen, S. Nikolov, C. Hassager, and J. Kjaergaard, 'Cardiac In-Vivo Measurements Using Synthetic Transmit Aperture Ultrasound,' in Proc. IEEE Ultrason. Symp., 2006, pp. 1115-1118. [49] NVIDIA, NVIDIA CUDA Best Practices Guide 3.0 ed., 2010. [50] Intel. Available: http://www.intel.com/ [51] J. A. Jensen, 'Field: A program for simulating ultrasound systems,' in Proc. Med. Biol. Eng. Comp., 10th Nordic-Baltic Conference on Biomedical Imaging, Vol. 4, Supplement 1, Part 1, 1996, pp. 351–353. [52] J. A. Jensen, 'Simulation of advanced ultrasound systems using Field II,' in Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, 2004, pp. 636-639 Vol. 1. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46149 | - |
dc.description.abstract | 本研究提出陣列超音波成像的軟體實現架構,以軟體方法取代傳統陣列超音波的硬體電路。其優勢在於可以減少系統複雜度,也降低開發所需時間與成本。以CPU為基礎的軟體成像系統,其系統表現受到CPU架構限制,平行能力較低。本研究提出以GPU為基礎的架構,利用GPU的高平行能力與影像處理的優勢,並使用 CUDA來設計成像程式。成像功能則包含調相陣列成像、彩色都普勒影像與合成發射孔徑成像。
本軟體系統實現在由NVIDIA GeForce GTX 260顯示卡 與CPU為Intel core i7 920組成的電腦系統上。其扇形掃描在使用128單元、2048點接收長度與由189條波束組成影像的測試資料可達到每秒42張的成像率。相同格式的測試資料在使用每張影像16次發射的合成發射孔徑技術可達每秒40張的成像率。彩色都普勒成像使用128單元、2048點接收長度與181條波束的B-mode測試資料與1024點長度,90條波束、每方向發射8次的流速資料。使用傳統方法的成像率為每秒14張,使用雙波束法則可達到每秒20張。 軟體系統大量的傳輸資料需求可能會成為成像速度的瓶頸,為了達到即時成像,本研究提出壓縮傳輸資料的方法來克服傳輸資料速度的限制。使用JPEG技術對傳輸資料壓縮後合成影像並評估影像品質,並以影像點平均誤差小於4dB做為指標。JPEG在壓縮10倍後仍能保有可接受品質,使用JPEG2000技術則可進一步壓縮到20倍。壓縮率太高則會造成信號失真,降低影像品質。 為了做到即時合成發射孔徑流速偵測,本研究也探討彩色都普勒影像應用在合成發射孔徑流速偵測的可能性,使用field II模擬超音波信號的方法並比較各種方法的偵測準確度。雖然合成發射孔徑流速偵測的可以每次發射都合成一張流速影像,且在無雜訊時可以達到比平面波或使用一半樣本數計算流速傳統方法低約1%內的誤差率,但在SNR為20dB時準確率會低於另外兩個方法。其最大可偵測流速亦會受限,為傳統方法的一半。低誤差耐受性與最大可偵測流速成為合成發射孔徑流速偵測的主要限制。 | zh_TW |
dc.description.abstract | In this research, we investigate software-based ultrasonic array imaging. The advantages of a software-based architecture include lower hardware complexity, development time and cost. size. Compared to CPU-based systems, with which performance is often limited by its inadequate parallelism, the GPU-based architecture has the potential of increasing computation speed significantly. In this research, CUDA GPU-based parallel programming is used. The imaging tasks under investigation include phased array imaging, color Doppler, and synthetic transmit aperture (STA) imaging.
The software is implemented with NVIDIA GeForce GTX 260 and Intel core i7 920 CPU. Frame rate of this system is 42 fps with a 128 elements array transducer, 2048 samples per firing and 189 beams per image. Frame rate of STA imaging is 40 fps with 16 firings per image. Color Doppler imaging is tested with similar B-mode data, and flow data consisted of 1024 samples per firing, 90 beams and an ensemble of 8 firings per beam. The frame rate is 14 fps with single beam, and it is 20 fps with dual beams. The large data transfer requirement of software-based system may be a bottleneck to achieve real time imaging. In this research, we also investigated channel data compression methods to overcome the limitation. In channel data compression, when the average error is under 4dB, the maximum acceptable compression ratio is 10 with JPEG and 20 with JPEG2000. In order to realize real time STA flow estimation, accuracy of STA color Doppler is investigated by simulations. Field II is used to compare accuracy of various flow estimations. The frame rate of STA color Doppler is equal to PRF, and the error is about 1% lower than plane wave and conventional method with half autocorrelation samples. However, the accuracy of STA color Doppler is lower than the other methods when SNR is 20dB or lower. Also, the maximum detectable velocity with STA color Doppler is half of that with conventional method. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T04:55:40Z (GMT). No. of bitstreams: 1 ntu-99-R97945002-1.pdf: 6133982 bytes, checksum: 0e4c1e5526115a102009fbf4af935cec (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | 摘要..........................................................................................................II
Abstract.................................................................................................IV 目錄..........................................................................................................VI 圖目錄...................................................................................................IX 表目錄......................................................................................................XI 第一章 緒論............................................................................................1 1.1 陣列超音波系統................................ .....................................................1 1.1.1 陣列超音波系統架構...................................................................1 1.1.2 陣列超音波系統的發展限制…...................................................3 1.2 軟體基礎超音波系統….........................................................................4 1.2.1 CPU平行處理技術…...................................................................4 1.2.2 軟體基礎超音波系統限制...........................................................5 1.2.3 GPGPU平行處理技術............. ..................................................8 1.3 合成發射孔徑成像.............................. ................................................11 1.4 血流偵測...............................................................................................14 1.4.1 血流偵測限制.............................................................................14 1.4.2 血流偵測成像率改善方法................................ ........................14 1.5 研究動機與目標................................... ...............................................16 1.6 論文架構...............................................................................................17 第二章 超音波成像與血流偵測原理...............................................................18 2.1 波束形成...............................................................................................18 2.2 傳統成像方法.......................................................................................22 2.3 合成發射孔徑成像...............................................................................24 2.4 流速偵測原理.......................................................................................26 2.4.1 血流偵測限制.............................................................................26 2.4.2 超音波血流偵測.........................................................................27 2.5 彩色都卜勒血流偵測...........................................................................30 2.6 斑點追蹤法...........................................................................................32 2.7 合成發射孔徑血流偵測.......................................................................34 2.7.1 遞迴成像.....................................................................................34 2.7.2 點散布函數變化.........................................................................36 第三章 CUDA平行運算架構............................................................................39 3.1 SIMT平行運算架構.............................................................................39 3.2 效能提升設計.......................................................................................43 3.2.1 平行度最佳化............................................................................43 3.2.2 傳輸頻寬最佳化........................................................................43 3.2.3 記憶體配置最佳化....................................................................45 3.2.4 核心使用率最佳化....................................................................47 第四章 系統架構與流速偵測模擬方法...........................................................50 4.1 軟體基礎陣列超音波系統架構..........................................................50 4.1.1 系統硬體設備............................................................................50 4.1.2 基本成像流程............................................................................53 4.1.3 調相陣列成像............................................................................54 4.1.4 合成發射孔徑成像....................................................................57 4.1.5 彩色都普勒成像......................................... ..............................59 4.1.6 傳輸資料壓縮............................................................................61 4.2 合成發射孔徑流速偵測方法..............................................................62 4.2.1 流體模擬設計............................................................................62 4.2.2 流速偵測方法............................................................................63 第五章 結果與討論...........................................................................................65 5.1 軟體基礎陣列超音波成像..................................................................65 5.1.1 調相陣列成像速度表現............................................................65 5.1.2 合成發射孔徑成像速度表現....................................................67 5.1.3 成像速度討論............................................................................67 5.1.4 彩色都普勒影像成像速度表現................................................72 5.1.5 傳輸資料壓縮表現....................................................................74 5.1.6 扇形掃描合成發射孔徑影像品質討論....................................77 5.2 合成發射孔徑流速偵測......................................................................79 5.2.1 流速偵測模擬結果....................................................................79 5.2.2 流速偵測限制............................................................................82 第六章 結論與未來工作...................................................................................85 6.1 軟體基礎陣列超音波成像..................................................................85 6.2 超音波信號壓縮技術….....................................................................86 6.3 合成發射孔徑流速偵測......................................................................87 文獻回顧...............................................................................................................88 | |
dc.language.iso | zh-TW | |
dc.title | 以軟體基礎實現醫用陣列超音波影像 | zh_TW |
dc.title | Software-Based Implementation of Ultrasonic Array Imaging | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 江惠華,王士豪,郭柏齡,沈哲州 | |
dc.subject.keyword | 陣列超音波成像,軟體平行技術,CUDA,合成發射孔徑成像,合成發射孔徑流速偵測,超音波信號壓縮, | zh_TW |
dc.subject.keyword | ultrasonic array imaging,software parallel programming,CUDA,synthetic transmit aperture imaging,synthetic transmit aperture flow estimation,ultrasonic signal compression, | en |
dc.relation.page | 91 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-07-30 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
顯示於系所單位: | 生醫電子與資訊學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-99-1.pdf 目前未授權公開取用 | 5.99 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。