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A numerical study concerning brain stroke detection by microwave imaging systems

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Abstract

In this paper, a numerical study devoted to evaluate the application of a microwave imaging method for brain stroke detection is described. First of all, suitable operating conditions for the imaging system are defined by solving the forward electromagnetic scattering problem with respect to simplified configurations and analyzing the interactions between an illuminating electromagnetic wave at microwave frequencies and the biological tissues inside the head. Then, preliminary inversion results are obtained by applying an imaging procedure based on an iterative Gauss-Newton scheme to a realistic model of the human head. The proposed imaging algorithm is able to deal with the nonlinear and ill-posed problem associated to the integral equations describing the inverse scattering problem. The aim of the inversion procedure is related to the determination of the presence of a hemorrhagic brain stroke by retrieving the distributions of the dielectric parameters of the human tissues inside a slice of the head model.

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References

  1. Barbeito A, Painho M, Cabral P, O’Neill JG (2017) Beyond Digital human body atlases: segmenting an integrated 3D topological model of the human body. Int J E-Health Med Commun 8:19–36. doi:10.4018/IJEHMC.2017010102

    Article  Google Scholar 

  2. Bertero M, Boccacci P (1998) Introduction to inverse problems in imaging. IOP Publishing, Bristol

    Book  MATH  Google Scholar 

  3. Bialkowski K, Ireland D, Abbosh A (2013) Microwave imaging for brain stroke detection using born iterative method. IET Microw Antennas Propag 7:909–915. doi:10.1049/iet-map.2013.0054

    Article  Google Scholar 

  4. Bialkowski KS, Abbosh AM, Mohammed BJ (2015) Radar-based time-domain head imaging using database of effective dielectric constant. Electron Lett 51:1574–1576. doi:10.1049/el.2015.1376

    Article  Google Scholar 

  5. Bozza G, Estatico C, Pastorino M, Randazzo A (2007) Microwave imaging for nondestructive testing of dielectric structures: numerical simulations using an inexact Newton technique. Mater Eval 65:917–922

    Google Scholar 

  6. Bozza G, Estatico C, Pastorino M, Randazzo A (2007) Application of an inexact-Newton method within the second-order born approximation to buried objects. IEEE Geosci Remote Sens Lett 4:51–55. doi:10.1109/LGRS.2006.885864

    Article  Google Scholar 

  7. Bozza G, Estatico C, Massa A et al (2007) Short-range image-based method for the inspection of strong scatterers using microwaves. IEEE Trans Instrum Meas 56:1181–1188. doi:10.1109/TIM.2007.900127

    Article  Google Scholar 

  8. Burfeindt MJ, Shea JD, Van Veen BD, Hagness SC (2014) Beamforming-enhanced inverse scattering for microwave breast imaging. IEEE Trans Antennas Propag 62:5126–5132. doi:10.1109/TAP.2014.2344096

    Article  MATH  Google Scholar 

  9. Byrne D, Craddock IJ (2015) Time-domain wideband adaptive Beamforming for radar breast imaging. IEEE Trans Antennas Propag 63:1725–1735. doi:10.1109/TAP.2015.2398125

    Article  MathSciNet  MATH  Google Scholar 

  10. Caorsi S, Massa A, Pastorino M, Randazzo A (2003) Electromagnetic detection of dielectric scatterers using phaseless synthetic and real data and the memetic algorithm. IEEE Trans Geosci Remote Sens 41:2745–2753. doi:10.1109/TGRS.2003.815676

    Article  Google Scholar 

  11. Caorsi S, Massa A, Pastorino M, Randazzo A, Rosani A (2004) A reconstruction procedure for microwave nondestructive evaluation based on a numerically computed Green’s function. IEEE Trans Instrum Meas 53(4):987–992. doi:10.1109/TIM.2004.831446

  12. Catapano I, Randazzo A, Slob E, Solimene R (2015) GPR imaging via qualitative and quantitative approaches. In: Benedetto A, Pajewski L (eds) Civ. Eng. Appl. Ground Penetrating radar. Springer, Cham, pp 239–280

    Google Scholar 

  13. Chew WC (1995) Waves and fields in inhomogeneous media. IEEE Press, New York

    Google Scholar 

  14. Donnell KM, Zoughi R (2012) Detection of corrosion in reinforcing steel bars using microwave dual-loaded differential modulated Scatterer technique. IEEE Trans Instrum Meas 61:1–16. doi:10.1109/TIM.2012.2200822

    Article  Google Scholar 

  15. Estatico C, Pastorino M, Randazzo A (2012) A novel microwave imaging approach based on regularization in Lp Banach spaces. IEEE Trans Antennas Propag 60:3373–3381. doi:10.1109/TAP.2012.2196925

    Article  MATH  Google Scholar 

  16. Estatico C, Fedeli A, Pastorino M, Randazzo A (2015) A multifrequency inexact-Newton method in Lp Banach spaces for buried objects detection. IEEE Trans Antennas Propag 63:4198–4204. doi:10.1109/TAP.2015.2446995

    Article  Google Scholar 

  17. Fear EC, Bourqui J, Curtis C et al (2013) Microwave breast imaging with a Monostatic radar-based system: a study of application to patients. IEEE Trans Microw Theory Tech 61:2119–2128. doi:10.1109/TMTT.2013.2255884

    Article  Google Scholar 

  18. Gabriel S, Lau RW, Gabriel C (1996) The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. Phys Med Biol 41:2251–2269. doi:10.1088/0031-9155/41/11/002

    Article  Google Scholar 

  19. Guo L, Abbosh AM (2015) Microwave imaging of Nonsparse domains using born iterative method with wavelet transform and block sparse Bayesian learning. IEEE Trans Antennas Propag 63:4877–4888. doi:10.1109/TAP.2015.2473000

    Article  MathSciNet  Google Scholar 

  20. Hacke W, Kaste M, Bluhmki E et al (2008) Thrombolysis with Alteplase 3 to 4.5 hours after acute ischemic stroke. N Engl J Med 359:1317–1329. doi:10.1056/NEJMoa0804656

    Article  Google Scholar 

  21. Hossain MD, Mohan AS, Abedin MJ (2013) Beamspace time-reversal microwave imaging for breast cancer detection. IEEE Antennas Wirel Propag Lett 12:241–244. doi:10.1109/LAWP.2013.2247018

    Article  Google Scholar 

  22. Ireland D, Bialkowski ME (2011) Microwave head imaging for stroke detection. Prog Electromagn Res M 21:163–175. doi:10.2528/PIERM11082907

    Article  Google Scholar 

  23. Kim YJ, Jofre L, De Flaviis F, Feng MQ (2003) Microwave reflection tomographic array for damage detection of civil structures. IEEE Trans Antennas Propag 51:3022–3032. doi:10.1109/TAP.2003.818786

    Article  Google Scholar 

  24. Kwiatkowski TG, Libman RB, Frankel M et al (1999) Effects of tissue plasminogen activator for acute ischemic stroke at one year. N Engl J Med 340:1781–1787. doi:10.1056/NEJM199906103402302

    Article  Google Scholar 

  25. Larsen LE, Jacobi JH, IEEE Microwave Theory and Techniques Society (1986) Medical applications of microwave imaging. IEEE Press, New York

    Google Scholar 

  26. Lazebnik M, McCartney L, Popovic D et al (2007) A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries. Phys Med Biol 52:2637–2656. doi:10.1088/0031-9155/52/10/001

    Article  Google Scholar 

  27. Manirabona A, Fourati LC, Boudjit S (2017) Investigation on healthcare monitoring systems: innovative services and applications. Int J E-Health Med Commun 8:1–18. doi:10.4018/IJEHMC.2017010101

    Article  Google Scholar 

  28. Miao Z, Kosmas P (2017) Multiple-frequency DBIM-TwIST algorithm for microwave breast imaging. IEEE Trans Antennas Propag 65(5):2507–2516. doi:10.1109/TAP.2017.2679067

  29. Mohammed BJ, Abbosh AM, Mustafa S, Ireland D (2014) Microwave system for head imaging. IEEE Trans Instrum Meas 63:117–123. doi:10.1109/TIM.2013.2277562

    Article  Google Scholar 

  30. Monleone R, Pastorino M, Fortuny-Guasch J et al (2012) Impact of background noise on dielectric reconstructions obtained by a prototype of microwave axial tomograph. IEEE Trans Instrum Meas 61:140–148. doi:10.1109/TIM.2011.2159144

    Article  Google Scholar 

  31. Mustafa S, Mohammed B, Abbosh A (2013) Novel preprocessing techniques for accurate microwave imaging of human brain. IEEE Antennas Wirel Propag Lett 12:460–463. doi:10.1109/LAWP.2013.2255095

    Article  Google Scholar 

  32. Mustafa S, Abbosh AM, Nguyen PT (2014) Modeling human head tissues using fourth-order Debye model in convolution-based three-dimensional finite-difference time-domain. IEEE Trans Antennas Propag 62:1354–1361. doi:10.1109/TAP.2013.2296323

    Article  MathSciNet  MATH  Google Scholar 

  33. Nikolova N (2011) Microwave imaging for breast cancer. IEEE Microw Mag 12:78–94. doi:10.1109/MMM.2011.942702

    Article  Google Scholar 

  34. O’Halloran M, Jones E, Glavin M (2010) Quasi-Multistatic MIST Beamforming for the early detection of breast cancer. IEEE Trans Biomed Eng 57:830–840. doi:10.1109/TBME.2009.2016392

    Article  Google Scholar 

  35. Pastorino M (2010) Microwave imaging. Wiley, Hoboken

    Book  Google Scholar 

  36. Pastorino M, Randazzo A, Fedeli A et al (2015) A microwave tomographic system for wood characterization in the forest products industry. Wood Mater Sci Eng 10:75–85. doi:10.1080/17480272.2014.898696

    Article  Google Scholar 

  37. Persson M, Fhager A, Trefna HD et al (2014) Microwave-based stroke diagnosis making global Prehospital thrombolytic treatment possible. IEEE Trans Biomed Eng 61:2806–2817. doi:10.1109/TBME.2014.2330554

    Article  Google Scholar 

  38. Porter E, Coates M, Popovic M (2016) An early clinical study of time-domain microwave radar for breast health monitoring. IEEE Trans Biomed Eng 63:530–539. doi:10.1109/TBME.2015.2465867

    Article  Google Scholar 

  39. Ren K, Burkholder RJ (2016) A uniform diffraction tomographic imaging algorithm for near-field microwave scanning through stratified media. IEEE Trans Antennas Propag 64:5198–5207. doi:10.1109/TAP.2016.2617358

    Article  Google Scholar 

  40. Ricci E, Di Domenico S, Cianca E, Rossi T (2015) Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, pp 1930–1933

  41. Richmond J (1965) Scattering by a dielectric cylinder of arbitrary cross section shape. IEEE Trans Antennas Propag 13:334–341. doi:10.1109/TAP.1965.1138427

    Article  Google Scholar 

  42. Riechers RG, Pasala KM, Ling GSF (1998) Microwave detection system for locating hemorrhage sites within the cranium and other regions. In: Proc 15th Annu AESSIEEE Dayt, Sect Symp Sens World Analog Sens Syst Spectr, pp 1–12

  43. Scapaticci R, Di Donato L, Catapano I, Crocco L (2012) A feasibility study on microwave imaging for brain stroke monitoring. Prog Electromagn Res B 40:305–324. doi:10.2528/PIERB12022006

    Article  Google Scholar 

  44. Semenov SY, Corfield DR (2008) Microwave tomography for brain imaging: feasibility assessment for stroke detection. Int J Antennas Propag. doi:10.1155/2008/254830

  45. Semenov S, Hopfer M, Planas R, et al (2016) Electromagnetic tomography for brain imaging: 3D reconstruction of stroke in a human head phantom. In: Proc 2016 I.E. Conf Antenna Meas Appl CAMA pp 1–4

  46. Shea JD, Van Veen BD, Hagness SC (2012) A TSVD analysis of microwave inverse scattering for breast imaging. IEEE Trans Biomed Eng 59:936–945. doi:10.1109/TBME.2011.2176727

    Article  Google Scholar 

  47. Zamani A, Abbosh AM, Mobashsher AT (2016) Fast frequency-based multistatic microwave imaging algorithm with application to brain injury detection. IEEE Trans Microw Theory Tech 64(2):653–662. doi:10.1109/TMTT.2015.2513398

  48. Zhang W, Hoorfar A (2014) Three-dimensional synthetic aperture radar imaging through multilayered walls. IEEE Trans Antennas Propag 62:459–462. doi:10.1109/TAP.2013.2287274

    Article  Google Scholar 

  49. Zubal IG, Harrell CR, Smith EO et al (1994) Computerized three-dimensional segmented human anatomy. Med Phys 21:299–302. doi:10.1118/1.597290

    Article  Google Scholar 

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Acknowledgments

The present work is partially supported by Compagnia di San Paolo, Italy.

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Authors and Affiliations

  1. Department of Electrical, Electronic, Telecommunications Engineering, and Naval Architecture, University of Genoa, Via Opera Pia 11A, 16145, Genoa, Italy

    Igor Bisio, Alessandro Fedeli, Fabio Lavagetto, Matteo Pastorino, Andrea Randazzo, Andrea Sciarrone & Emanuele Tavanti

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  1. Igor Bisio
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Correspondence to Matteo Pastorino.

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Bisio, I., Fedeli, A., Lavagetto, F. et al. A numerical study concerning brain stroke detection by microwave imaging systems. Multimed Tools Appl 77, 9341–9363 (2018). https://doi.org/10.1007/s11042-017-4867-7

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