Untitled không G I – I I – I I I nhi t tình n t và Vi h th – T H H G H – H G G n ph m c a quá trinh nghiên c u, tìm hi u c i s ng d n và ch b o c a các th y môn, trong khoa và các b u hay các công trì[.]
không G I I – – I I I I nhi t tình n – t Vi h th H H – T G H H G G n ph m c a trinh nghiên c u, tìm hi u c is ng d n ch b o c a th y môn, khoa b nghiên c u c làm lu n N u vi ph m, xin ch u m i trách nhi m u hay cơng trình I I .4 H HI H H G .1 H GI I HI U 1.1 T G 1.2 CH 1.3 T H H I G H H H G I G G G H G 2.1 BORN ITERATIVE METHOD (BIM) 2.2 DISTORTED BORN ITERATIVE METHOD (DBIM) 11 2.3 B I G 12 2.4 M H G H N BIM DBIM 14 2.4.1 14 2.4.2 18 2.4.3 21 H G 3.1 3.2 T H H G H 22 GI X G 4.1 M 4.2 V 22 I 24 28 H G HI H GI H I GI H G 28 41 .44 I I H H O 45 DANH BIM Born Iterative Method DBIM Distorted Born Iterative Method mm N ⃑ m/s ⃑ ⃑ ⃑ m/s H ⃑ ⃑ Pa Pa Pa rad/m 24 .25 .26 I .28 I - .28 I .30 I - .31 I .34 I - 34 I I 36 - 37 39 40 41 42 H H H 14 H H 14 H H 15 H 15 H H .16 H H 17 H H 17 H H 18 H H 19 H H 19 H H 20 H H 20 H I I 21 H th bi u di n m i liên h gi a s l n l p x sai s error (N1 = 10) 25 H th bi u di n m i liên h gi a s l n l p x sai s error (N1 =11) .26 H th bi u di n m i liên h gi a s l n l p x sai s error (N1 = 12) 27 H H .28 H 28 H 28 H 29 H 29 H H H I I 30 30 H 31 H 31 H 32 H 32 H H H I I 33 33 H .34 H 34) 35 H 35 H H I H I 36 36 H .37 H 38 H 38 H I I 39 H 40 H 40 H 41 H .42 H 30 43 H .43 1.1 (magnetic resonance imaging), Siêu âm (ultrasound) M m l n nh t c a CT cho phép kh o sát ph u trúc tinh t pc ng t , kí hi u MRI (magnetic resonance imaging) khơng t h u hi ng h p Hình nh CT cho ch ng r t t t Vì v y, hi E i ta k t h p CT v t o nh ch t o máy quét CT/PET v a cho hình nh gi i ph u v a kh c d ng tia X có tác h i x b nh nhân Tia X có kh Ngoài ra, giá c c a l n ch p CT r bào, v t c ch i v i s c kho c a ng l n có th I a c u trúc mô m õ i pháp khác, n MRI tr thành công c ch kh th c phát hi n) có th ch u d ng v i b nh nhân mang 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 Siêu âm (ultrasound) m o sát hình nh h c b ng cách cho m t ph n c ti p xúc v i sóng âm có t n s t o hình th Siêu âm khơng s d ng phóng x ion hóa (nh nh siêu âm c ghi nh n theo th i gian th c nên có th cho th y hình nh c u trúc s chuy ng c a b ph k c hình y m ch máu l -mode - ng cách nh nh t gi a hai v t ph n x mà chúng có th phân bi t rõ tín hi u d i hi n th phân gi d c tr c slice thickness) phân gi phân gi i G -mode 1.2 ồ H – E H Tuy – -11] H H H ồ I H – I 32 – õ H I I I (N = 22) I – – Conventional l ộ ế ợ Simulation parameters: Frequency = 1MHz N1 = 17, x = 1, N2 = 34 N = 34 Diameter of scatter area = 5*landa Percent of sound contrast 1% 5% Gaussian noise (SNR = 26 dB)Detector = 34, Transmiter = 64 H 33 H : I Iter err 0.5056 0.2421 0.1641 0.1411 688 giây : I - Iter err 0.2744 0.1531 0.0854 57.4 giây H H H H H 34 H H ồ I H – I õ 35 – H I I Simulation parameters: Frequency = 1MHz N1 = 20, x = 1, N2 = 40 N = 40 Diameter of scatter area = 5*landa Percent of sound contrast 1% 5% Gaussian noise (SNR = 26 dB) Detector = 40, Transmiter = 80 H H (N = 40) I Iter err 0.5498 0.2300 0.1616 0.1405 1730 giây 36 I - Iter err 0.2044 0.1260 0.0860 1379 giây H H H H h 4.24 H (N1 = 20, N = 40) 37 H (N1 = 20, N = 40) H ồ I õ H 25 – I 38 – H 25 I I 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 - conventional - propose 39 H 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 H 40 4.2 ng 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% I I – Conventional – Propose H H H 4.28: 41 H 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% H H 42 H 30 H -23% -15% 43 ĩ 44 cy– F H G W IEEE F damentals of digital ultrasonic pp 195– 217, July 1984 dings of the IEEE, vol 67, 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 - W sidelobe IEEE Transac-tions on Ultrasonics, Ferroelectrics, and Frequency 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, ment of ultrasound tomography for breast 5, pp 1375–1386, May 2005 H 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 IEEE ransactions on Medical Imaging, vol 24, no 3, pp 399–408, March 2005 [8] S A Johnson, T Abbott, R Bell, M Berggren, D Borup, D Robinson, J Wiskin, H tissue charac-terization using ultrasound speed and atten I vol 28, 2007, pp 147–154 [9] J Greenleaf, J Ylitalo, and J Gisvold, IEEE E 4, pp 27–32, December 1987 for ine and Biology Mag-azine, vol.6, no [10] M P Andre, H S Janee, P J Martin, G P Otto, B A Spivey , and D.A H -speed data acquisition in a diffraction tomography sys-tem employing largeInternational 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, nonI 2007, pp.183– 194 45 [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 Frequency 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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