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ĐẠI HỌC QUỐC GIA HÀ NỘI TRƯỜNG ĐẠI HỌC CÔNG NGHỆ Đ NG N NG C N NG Ư NG CH T Ư NG NH CH I NG HƯ NG H N I N THẠC CÔNG NGHỆ ĐIỆN T HÀ N I - 2013 C T – I N THÔNG ĐẠI HỌC QUỐC GIA HÀ NỘI TRƯỜNG ĐẠI HỌC CÔNG NGHỆ Đ NG N NG C NG Ư NG CH T Ư NG NH CH I NG HƯ NG H N I NGÀNH C NG NGH ĐI N CHUYÊN NGÀNH HU C T – I N H NG ĐI N Ố: 60 52 70 N N THẠC NGƯỜI HƯ NG CÔNG NGHỆ ĐIỆN T N H HỌC T HÀ N I - 2013 – I N THÔNG TR N Đ C T N ƯƠ .5 1.1 T 1.2 C 1.3 T Ư ƯƠ NG 2.1 BORN ITERATIVE METHOD (BIM) 2.2 DISTORTED BORN ITERATIVE METHOD (DBIM) 11 2.3 B Ư 12 2.4 M N BIM DBIM 14 2.4.1 14 2.4.2 18 2.4.3 21 ƯƠ 3.1 3.2 T ƯƠ 4.1 M 4.2 V ƯƠ T 22 .22 X Ư 24 .28 .28 42 Ư .45 O .46 BIM Born Iterative Method DBIM Distorted Born Iterative Method mm (pixel) N /ngang m/s m/s Pa ) Pa Pa rad/m (N1 = 10) .24 (N1 = 11) .25 (N1 = 12) .26 (N = 20) 28 - (N1 = 10,N2 = 20) 28 (N = 22) 31 - (N1 = 11,N2 = 22) 32 (N = 34) 35 - (N1 = 17, N2 = 34) 35 (N = 40) 37 - (N1 = 20, N2 = 40) 38 40 41 .42 .43 .8 14 .14 15 .15 (N=17) .16 17 17 18 19 19 20 20 21 th biểu diễn m s l n l error (N1 = 10) 25 th biểu diễn m s l n l error (N1 =11) .26 th biểu diễn m s l n l error (N1 = 12) 27 (N = 20) 28 (N1 = 10, N = 20) 29 (N1 = 10, N = 20) .29 (N1 = 10, N = 20) .30 (N1 = 10, N = 20) .30 (N =20) .31 (N = 22) 31 (N1 = 11, N = 22) 32 (N1 = 11, N = 22) 32 (N1 = 11, N = 22) 33 (N1 = 11, N = 22) 33 (N = 22) 34 (N=34) 34 (N1 = 17, N = 34) .35 (N1 = 17, N = 34) 36 (N1 = 17, N = 34) 36 (N = 34) 37 (N = 40) 37 (N1 = 20, N = 40) .38 (N1 = 20, N = 40) 39 (N1 = 20, N = 40) 39 (N = 40) 40 41 41 .42 43 4.30 44 4.31 .44 1.1 (magnetic resonance imaging), M ểm l n nh t c pc tinh t é ng t ỏ hữu hi ng h v y, hi i ta k t h p CT v ểt é / E c b h ú u MRI (magnetic resonance imaging) nh CT cho ch ng r t t E ù ể t o nh ch nh gi i phẫu v a kh c ch ửd ix ng l c a l n ch Ư ể ac ú ể õ i n MRI tr th ể ch ể thể ể ch u d ng v i v i s c khoẻ c a thể thai i, ct ob nh th i kỳ t b ng kim lo i c ng c a t ng m u, tr th t c n thi t nh h c b m t ph n c ể ti ú thể ửd c ghi nh n theo th i gian thự ns chuyể ể kể c ng c ểt ể cho th ph nh c ú ự ò y ò ự l ể 1910 ữ -mode - ự “ ể ể ỏ nh t hai v t ph n x “ ú ng ể õ ud hiển th i d c tr ) ù ể ự Tuy ự ể ò ò ắ ể ể ể ỏ ắ ắ ự ể ù ể ò ữ -mode ể ể ữ ắ ù 1.2 ắ ự ự ữ ắ ể ự ắ ể – ẫ ò ỏ ễ E ắ - ắ – ắ ắ “ ể ữ ự ữ ù ự [9-11] ể ù ự ể ù MHz) Tr ù ú ú ù ắ ắ ắ ú ể ể ) ò nội suy kết hợp với xấp xỉ Born nh m lu ể xu u ch p n ù ắ ong b -23] i nhữ l p t 1.3 ò ắ ữ (Distorted born iterative method) ể ù ữ ữ 4.13 (N1 = 11, N = 22) 4.14 (N1 = 11, N = 22) , 4.15 ỏ – é – ò é ỏ 33 é 4.15 - - (N = 22) – ò – 20% so v ộ ế ợ 9: ỏ : = 1MHz N1 = 17, x = 1, N2 = 34 N = 34 ù = 5*lamda 1% 5% Gaussian noise (SNR = 26 dB)Detector = 34, Transmiter = 64 (N=34) 34 4.8: (N = 34) Iter err 0.5056 0.2421 0.1641 0.1411 688 giây 4.9: - (N1 = 17, N2 = 34) Iter err 0.2744 0.1531 0.0854 57.4 giây 4.17 4.19 4.17 (N1 = 17, N = 34) 35 4.18 (N1 = 17, N = 34) 4.19 (N1 = 17, N = 34) , 4.20 – ỏ en é ỏ ỏ é – ò 36 é 4.20 (N = 34) 10: ỏ : = 1MHz N1 = 20, x = 1, N2 = 40 N = 40 ù = 5*lamda 1% 5% Gaussian noise (SNR = 26 dB) Detector = 40, Transmiter = 80 (N = 40) : (N = 40) Iter err 0.5498 0.2300 0.1616 0.1405 1730 giây 37 : - (N1 = 20, N2 = 40) Iter err 0.2044 0.1260 0.0860 1379 giây 4.23 h 4.24 4.22 (N1 = 20, N = 40) 38 4.23 (N1 = 20, N = 40) 4.24 (N1 = 20, N = 40) ồ 4.25 ỏ – é – ỏ ò é ỏ é 39 4.25 (N = 40) : i g g y ig 4.12: T N 20 22 24 26 28 30 Err1 0.1059 0.1004 0.1015 0.1321 0.1340 0.1470 Err2 0.0346 0.0475 0.0180 0.0336 0.0319 0.0467 E E - 40 i 4.13: T N 20 22 24 26 28 30 Err1 0.1779 0.1778 0.1461 0.1792 0.1493 0.1673 Err2 0.0534 0.0779 0.0347 0.0710 0.0597 0.1217 41 y i g g i g g g y y g i g i g g 4.2 g g y ig 4.14: T N 20 22 24 26 28 30 T1 46.16 71.68 113.87 178.12 264.18 390.23 T2 36.12 57.35 89.50 139.21 211.47 301.07 10.04 14.33 23.67 38.91 52.71 89.16 21.75% 20% 20.79% 21.84% 19.95% 22.85% – – ể ễ 4.29 4.28: 42 4.29 i 4.15: T N 20 22 24 26 28 30 T1 75.24 124.23 194.00 291.38 435.25 620.29 T2 66.46 105.47 164.89 249.68 370.34 525.68 8.78 18.76 29.11 41.7 64.91 91.64 11.67% 15.10% 15.01% 14.31% 14.91% 14.77% ể ễ ể 4.31 43 4.30 4.31 ữ 20-23% - 44 ắ ữ ể ể é ù 3, Win7 – 64 bits, ram 4gb ĩ ể ể ực y – ữ ự 45 ữ ự F W “F damentals of digital ultrasonic processing, EEE 217, July 1984 pp 195– “ EEE no 4, pp 484–495, April 1979 [3] G S Kino, Acoustic Waves: Devices, Imaging, and Analog Signal Processing Englewood Cliffs, NJ: Prentice Hall, 1987 Z levels: Part I Ferroelectrics, and “W sidelobe EEE Transac-tions on Ultrasonics, Contr ol, vol 40, no 6, pp 747–753, November 1993 [5] N Duric, P Littrup, A Babkin, D Chambers, S Azevedo, A Kalinin, R.Pevzner, M Tokarev, E Holsapple, O Rama, tomography for breast 5, pp 1375–1386, May 2005 “ “ ment of ultrasound using transmission ultra-sound: Reconstructing tissue parameters o in International Conference on BioMedical Engineering and Informatics, vol 2, 2008, pp 708–712 [7] J.-W Jeong, T.-S Kim, D C Shin, S Do, M Singh, and V Z Marmarelis, “ tissue differentiation using multiband signatures of high resolution ul-trasonic transmiss 399–408, March 2005 EEE ransactions on Medical Imaging, vol 24, no 3, pp [8] S A Johnson, T Abbott, R Bell, M Berggren, D Borup, D Robinson, J Wiskin, “ tissue charac-terization using ultrasound speed and atten vol 28, 2007, pp 147–154 [9] J Greenleaf, J Ylitalo, and J Gisvold, “ for EEE E ine and Biology Mag-azine, vol.6, no 4, pp 27–32, December 1987 [10] M P Andre, H S Janee, P J Martin, G P Otto, B A Spivey , and D.A “ -speed data acquisition in a diffraction tomography sys-tem employing largenternational Journal of Imaging Systems and Technology, vol 8, no 1, pp 137–147, 1997 [11] J Wiskin, D Borup, S Johnson, M Berggren, T Abbott, and R Hanover, “F wave, non2007, pp.183– 194 46 [12] R J Lavarello and M L Oelze: Tomographic Reconstruction of ThreeDimensional Volumes Using the Distorted Born Iterative Method IEEE Transactions on Medical Imaging, 28, 2009, pp 1643-1653 [13] Lavarello Robert: New Developments on Quantitative Imaging Using Ultrasonic Waves University of Illinois at Urbana-Champaign, 2009 [14] http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method [15] M T Heath, Scientific Computing: An Introductory Survey New York, NY: McGraw-Hill, 2002 [16] Lavarello R, Oelze M (2008) A study on the reconstruction of moderate contrast targets using the distorted Born iterative method IEEE Transaction of Ultrasonic, Ferroelectric, and Control 55:112-124 [17] Devaney AJ (1982) Inversion formula for inverse scattering within the Born approximation Optics Letters 7:111-112 [18] http://tech-algorithm.com/articles/nearest-neighbor-image-scaling/ [19] Martin, R., Noise power spectral density estimation based on optimal smoothing and minimum statistics, IEEE Transactions on Speech and Audio Processing, Vol 9, 2001, pp 504 - 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