基于FDTD方法的早期乳腺癌微波检测方案研究
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摘要
乳腺癌是危害女性健康的常见恶性肿瘤疾病,其发病率居女性恶性肿瘤的第一位,早期检测被认为是降低其死亡率的重要途径,乳腺癌成像技术已成为当前国内外医学影像学研究的一个焦点。目前乳腺癌常规成像技术如X线成像,超声成像等均存在各种局限性,而微波频段下正常乳房组织和恶性肿瘤组织的电磁特性差异明显(远大于现有成像技术所利用的特性差异),这种差异为微波近场检测乳腺癌提供了物理基础。乳腺癌微波成像技术研究主要集中在有源微波成像方法,根据微波照射物体得到的散射场解决逆散射问题来进行成像。
本文介绍了常用的乳腺癌检测方法并分析了它们的优缺点,详细分析了正常乳房组织和癌变组织的电磁特性差异,在微波频段,它们的介电常数和电导率差异均在5倍以上,正常乳房组织比癌变组织更加“透明”,这就是微波检测乳腺癌的物理基础。微波成像方法有有源,无源及微波超声混合方法,本文分别做了介绍,并针对有源微波成像中的微波断层成像方法和共焦微波成像方法做了详细探讨,分析了其算法、仿真及实际系统。
本文主要利用时域有限差分方法(FDTD)进行微波乳腺癌成像方法的研究,首先利用FDTD算法及一种非分裂场的完全匹配层(PML)吸收边界条件进行了一些基础的电磁仿真,然后建立了两种数字乳房模型,长方体乳房模型及基于核磁共振成像(MRI)数据的半椭球乳房模型,仿真分析了两种模型在微波照射下的电磁特性,分析了微波探测乳腺癌的可行性。
针对逆散射成像中为解决病态及非线性问题造成计算量大计算时间长的问题,本文提出了一种可用于初步定位肿瘤位置的方案。此方案是将网格粗分,逐个试验肿瘤可能存在的位置,通过FDTD计算与测量值相比较,找出肿瘤的大致位置。本文验证了此方案的可行性,并在各种实际情况下研究其稳定程度,结果表明,通过优化天线阵列,该方案在-10dB高频或随机干扰等情况下能较为准确定位肿瘤位置。
Breast cancer is a sarcomata disease which is harmful to the health of women. Its incidence is on the first place of all the malignant tumor of women and the mortality rate is high. Early detection is an important way to lower its mortality. Breast tumor detection technology has been a highlight of medical imaging science all over the world. At present common imaging technologies for breast cancer such as X-ray imaging and ultrasound imaging have their limitation in some case. There is distinct difference in electromagnetic properties between normal breast tissues and malignant tumor, far greater than the differences using in other imaging technologies. This difference is the physics foundation for microwave breast near-field detection. At present most of these researches is focus on the active microwave imaging, which is based on the solution of inverse scattering problem with the irradiation of microwave on the breast.
This paper introduces the common method of breast cancer detection, analyzing advantage and disadvantage of them. Then the differences between normal breast tissue and malignant tissues were detailed analyzed. Under the microwave band, these differences in dielectric constant and conductivity were all above five times. This phenomenon induces the normal breast tissues is more translucent than malignant tissues in the irradiation of microwave. This is the physical basis of microwave detection for breast cancer. At microwave frequencies, breast imaging with passive, hybrid, and active methods has been explored for several decades. This paper introduces all of them and specifies the active microwave imaging method, including its algorithm, simulation and practical systems.
In this paper, the finite difference time domain (FDTD) method is used for the research of microwave breast imaging method. First, we have some basic simulations using FDTD and a unsplited perfect matched layer (PML) absorb boundary condition. Then two digital breast models were established, including the simple cubic breast model and the ellipsoid model based on magnetic resonance imaging (MRI) data. We analyze the property of two models under the irradiation of microwave by simulation, which is feasibility of detecting the breast cancer.
The inverse scattering problem brings the lager computation amount and time needing because in this process ill-posedness and nonlinear problems should be settled. Thus this paper presents a primary localization scheme. This scheme can be used for reducing computation time. We carve up the computation area using coarse grid. We test a possible grid as a tumor, and commutate using FDTD method, comparing the result with measurement data, and then the least difference will be funded indicating the practical tumor position. This paper proves the feasibility of this scheme, and proves the stability in several actual conditions. The result indicates that this scheme can localize the position of tumor in -10dB interfere by optimizing the antenna array.
本文介绍了常用的乳腺癌检测方法并分析了它们的优缺点,详细分析了正常乳房组织和癌变组织的电磁特性差异,在微波频段,它们的介电常数和电导率差异均在5倍以上,正常乳房组织比癌变组织更加“透明”,这就是微波检测乳腺癌的物理基础。微波成像方法有有源,无源及微波超声混合方法,本文分别做了介绍,并针对有源微波成像中的微波断层成像方法和共焦微波成像方法做了详细探讨,分析了其算法、仿真及实际系统。
本文主要利用时域有限差分方法(FDTD)进行微波乳腺癌成像方法的研究,首先利用FDTD算法及一种非分裂场的完全匹配层(PML)吸收边界条件进行了一些基础的电磁仿真,然后建立了两种数字乳房模型,长方体乳房模型及基于核磁共振成像(MRI)数据的半椭球乳房模型,仿真分析了两种模型在微波照射下的电磁特性,分析了微波探测乳腺癌的可行性。
针对逆散射成像中为解决病态及非线性问题造成计算量大计算时间长的问题,本文提出了一种可用于初步定位肿瘤位置的方案。此方案是将网格粗分,逐个试验肿瘤可能存在的位置,通过FDTD计算与测量值相比较,找出肿瘤的大致位置。本文验证了此方案的可行性,并在各种实际情况下研究其稳定程度,结果表明,通过优化天线阵列,该方案在-10dB高频或随机干扰等情况下能较为准确定位肿瘤位置。
Breast cancer is a sarcomata disease which is harmful to the health of women. Its incidence is on the first place of all the malignant tumor of women and the mortality rate is high. Early detection is an important way to lower its mortality. Breast tumor detection technology has been a highlight of medical imaging science all over the world. At present common imaging technologies for breast cancer such as X-ray imaging and ultrasound imaging have their limitation in some case. There is distinct difference in electromagnetic properties between normal breast tissues and malignant tumor, far greater than the differences using in other imaging technologies. This difference is the physics foundation for microwave breast near-field detection. At present most of these researches is focus on the active microwave imaging, which is based on the solution of inverse scattering problem with the irradiation of microwave on the breast.
This paper introduces the common method of breast cancer detection, analyzing advantage and disadvantage of them. Then the differences between normal breast tissue and malignant tissues were detailed analyzed. Under the microwave band, these differences in dielectric constant and conductivity were all above five times. This phenomenon induces the normal breast tissues is more translucent than malignant tissues in the irradiation of microwave. This is the physical basis of microwave detection for breast cancer. At microwave frequencies, breast imaging with passive, hybrid, and active methods has been explored for several decades. This paper introduces all of them and specifies the active microwave imaging method, including its algorithm, simulation and practical systems.
In this paper, the finite difference time domain (FDTD) method is used for the research of microwave breast imaging method. First, we have some basic simulations using FDTD and a unsplited perfect matched layer (PML) absorb boundary condition. Then two digital breast models were established, including the simple cubic breast model and the ellipsoid model based on magnetic resonance imaging (MRI) data. We analyze the property of two models under the irradiation of microwave by simulation, which is feasibility of detecting the breast cancer.
The inverse scattering problem brings the lager computation amount and time needing because in this process ill-posedness and nonlinear problems should be settled. Thus this paper presents a primary localization scheme. This scheme can be used for reducing computation time. We carve up the computation area using coarse grid. We test a possible grid as a tumor, and commutate using FDTD method, comparing the result with measurement data, and then the least difference will be funded indicating the practical tumor position. This paper proves the feasibility of this scheme, and proves the stability in several actual conditions. The result indicates that this scheme can localize the position of tumor in -10dB interfere by optimizing the antenna array.
引文
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[10]袁新颜,王炳高,齐春华.乳腺癌影像学诊断进展[J]山东医药:内科(上半月),2005,45(020):72-3
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[22] Joines WT, Zhang Y, Li C, et al. The measured electrical properties of normal and malignant human tissues from 50 to 900 MHz [J]Medical Physics, 1994, 21: 547
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[25]Kosmas P, Rappaport CM, Bishop E. Modeling with the FDTD method for microwave breast cancer detection [J]Microwave Theory and Techniques, IEEE Transactions on, 2004, 52(8 Part 2): 1890-7
[26] Gabriel C, Department of P, London King's C. Compilation of the Dielectric Properties of Body Tissues at RF and Microwave Frequencies: King's College, London, Department of Physics, 1996.
[27]Fear EC, Hagness SC, Meaney PM, et al. Enhancing breast tumor detection with near-field imaging [J]Microwave Magazine, IEEE, 2002, 3(1): 48-56
[28]Carr KL,Cevasco P,Dunlea P,et al.Radiometric sensing:an adjuvant to mammography to determine breastbiopsy[J]Microwave Symposium Digest.,2000IEEE MTT-S International,2000,2
[29]Kruger RA,Kopecky KK,Aisen AM,et al.Thermoacoustic CT with radio waves:A medical imaging paradigm[J]Radiology,1999,211(1):275-8
[30]Kruger RA,Kiser WL,Reinecke DR,et al.Thermoacoustic computed tomography of the breast at 434 MHz[J]Microwave Symposium Digest,1999 IEEE MTT-S International,1999,2
[31]Wang LV.Microwave-induced acoustic imaging of biological tissues[J]Review of Scientific Instruments,1999,70(9):3744
[32]Ku G,Wang LV.Scanning thermoacoustic tomography in biological tissue [J]Medical Physics,2000,27:1195
[33]Meaney PM,Paulsen KD,Pogue BW,et al.Microwave image reconstruction utilizing log-magnitude andunwrapped phase to improve high-contrast object recovery [J]Medical Imaging,IEEE Transactions on,2001,20(2):104-16
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[35]Pichot C,Jofre L,Peronnet G,et al.Active microwave imaging of inhomogeneous bodies[J]Antennas and Propagation,IEEE Transactions on[legacy,pre-1988],1985,33(4):416-25
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[2]Ries LAG HD,Krapcho M,Mariotto A,Miller BA,Feuer EJ,Clegg L,Eisner MP,Horner MJ,Howlader N,Hayat M,Hankey BF,Edwards BK(eds).SEER Cancer Statistics Review http://seer.cancer.gov/statfacts/html/breast.html,2007.
[3]张保宁。乳腺癌临床研究的回顾与展望[J]中华医学杂志,2005,85(001):7-8
[4]孙燕。临床肿瘤内科手册:人民卫生出版社,1991。
[5]李麟荪。医学影像学.南京:东南大学出版社,2002。
[6]阎鹏.乳腺癌的影像学检查[J]中外健康文摘:临床医师,2007,4(009):54-6
[7]Patlak M,Henderson IC,Lashof JC,et al.Mammography and Beyond:Developing Technologies for the Early Detection of Breast Cancer:A Non-Technical Summary:National Academies Press,2001.
[8]施俊,严壮志,蒋肾陕,et al.乳腺癌的影像普查技术进展[J]国际生物医学工程杂志,2007,30(001):28-31
[9]罗凤荣,李雁平。乳腺癌影像学诊断研究[J]医学综述,2005,11(9):856-8
[10]袁新颜,王炳高,齐春华.乳腺癌影像学诊断进展[J]山东医药:内科(上半月),2005,45(020):72-3
[11]王双坤。早期乳腺癌的影像学检查方法[J]继续医学教育,2006,20(025):30-5
[12]Friedrich M.MRI of the breast:state of the art[J]European Radiology,1998,8(5):707-25
[13]Nass SJ,Henderson C,Lashof JC.Mammography and beyond:developing technologies for the early detection of breast cancer:Institute of Medicine and Commission on Life Sciences[J]National Research Council,2001,
[14]Larsen LE,John H.Medical applications of microwave imaging:IEEE Press,1986.
[15]田雨波,钱鉴。微波近场成像检测乳腺癌及其微波热疗[J]微波学报,2003,19(003):72-8
[16] Chew WC. Imaging and inverse problems in electromagnetics [J]Advances in Computational Electrodynamics: The Finite-Difference Time-Domain Method, 653-702
[17]K.Lindsey SMLa. Dr Susan Love's Breast Book: HarperCollins publishers, 1995.
[18] Fear EC, Meaney PM, Stuchly MA. Microwaves for breast cancer detection? [J]Potentials, IEEE, 2003, 22(1): 12-8
[19] Foster KR, Schwan HP. Dielectric properties of tissues and biological materials: A critical review [J]Crit. Rev. Biomed. Eng, 1989,17(1): 25-104
[20]Chaudhary SS, Mishra RK, Swarup A, et al. Dielectric properties of normal & malignant human breast tissues at radiowave & microwave frequencies [J] Indian J Biochem Biophys, 1984,21(1): 76-9
[21]Surowiec AJ, Stuchly SS, Barr JR, et al. Dielectric properties of breast carcinoma and the surroundingtissues [J]Biomedical Engineering, IEEE Transactions on, 1988, 35(4): 257-63
[22] Joines WT, Zhang Y, Li C, et al. The measured electrical properties of normal and malignant human tissues from 50 to 900 MHz [J]Medical Physics, 1994, 21: 547
[23] Campbell AM. Dielectric properties of female human breast tissue measured in vitro at 3.2 GHz [J]Phys. Med, 1992, 37(1): 193-210
[24] Li X, Hagness SC. A confocal microwave imaging algorithm for breast cancer detection [J]Microwave and Wireless Components Letters, IEEE [see also IEEE Microwave and Guided Wave Letters], 2001,11 (3): 130-2
[25]Kosmas P, Rappaport CM, Bishop E. Modeling with the FDTD method for microwave breast cancer detection [J]Microwave Theory and Techniques, IEEE Transactions on, 2004, 52(8 Part 2): 1890-7
[26] Gabriel C, Department of P, London King's C. Compilation of the Dielectric Properties of Body Tissues at RF and Microwave Frequencies: King's College, London, Department of Physics, 1996.
[27]Fear EC, Hagness SC, Meaney PM, et al. Enhancing breast tumor detection with near-field imaging [J]Microwave Magazine, IEEE, 2002, 3(1): 48-56
[28]Carr KL,Cevasco P,Dunlea P,et al.Radiometric sensing:an adjuvant to mammography to determine breastbiopsy[J]Microwave Symposium Digest.,2000IEEE MTT-S International,2000,2
[29]Kruger RA,Kopecky KK,Aisen AM,et al.Thermoacoustic CT with radio waves:A medical imaging paradigm[J]Radiology,1999,211(1):275-8
[30]Kruger RA,Kiser WL,Reinecke DR,et al.Thermoacoustic computed tomography of the breast at 434 MHz[J]Microwave Symposium Digest,1999 IEEE MTT-S International,1999,2
[31]Wang LV.Microwave-induced acoustic imaging of biological tissues[J]Review of Scientific Instruments,1999,70(9):3744
[32]Ku G,Wang LV.Scanning thermoacoustic tomography in biological tissue [J]Medical Physics,2000,27:1195
[33]Meaney PM,Paulsen KD,Pogue BW,et al.Microwave image reconstruction utilizing log-magnitude andunwrapped phase to improve high-contrast object recovery [J]Medical Imaging,IEEE Transactions on,2001,20(2):104-16
[34]Semenov SY,Svenson RH,Boulyshev AE,et al.Microwave tomography:two-dimensional system for biological imaging[J]Biomedical Engineering,IEEE Transactions on,1996,43(9):869-77
[35]Pichot C,Jofre L,Peronnet G,et al.Active microwave imaging of inhomogeneous bodies[J]Antennas and Propagation,IEEE Transactions on[legacy,pre-1988],1985,33(4):416-25
[36]黄卡玛 赵.电磁场中的逆问题及应用。北京:科学出版社,2005.
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