Continuous Monitoring of Hemorrhagic Strokes via Differential Microwave Imaging
Continuous monitoring of a patient’s brain who is admitted to intensive care with a diagnosis of hemorrhagic stroke poses a great technological challenge. Existing medical imaging modalities such as CT and MRI that are extensively used for brain imaging are practically not suitable for these purposes. Nevertheless, microwave imaging as an emerging medical imaging technique can provide a safer and cost-effective alternative for continuous monitoring of the brain. In this context, differential microwave imaging with qualitative inverse scattering methods such as linear sampling method and factorization method is considered to determine evolution of intracranial hemorrhage without generating anatomical images. Through sequential S-parameters measurements performed on a brain phantom with a prototype microwave imaging system that cylindrically rotates two transceiver antennas around, feasibility of continuous monitoring of hemorrhagic strokes via microwave imaging is experimentally evaluated.
This work is supported by the Scientific and Research Council of Turkey (TUBITAK) under the grant numbers 113E977 and 216S415.
- 5.Akıncı, M.N., Çağlayan, T., Özgür, S., Alkaşı, U., Abbak, M., Çayören, M.: Experimental assessment of linear sampling and factorization methods for microwave imaging of concealed targets. Int. J. Antennas Propag. 2015, 1–11 (2015)Google Scholar
- 7.Bertero, M., Boccacci, P.: Introduction to Inverse Problems in Imaging, 1 edn. CRC Press (1998)Google Scholar
- 8.Birenbaum, D., Bancroft, L.W., Felsberg, G.J.: Imaging in acute stroke. West. J. Emerg. Med. 12(1), 67–76 (2010)Google Scholar
- 9.Cakoni, F., Colton, D.: A Qualitative Approach to Inverse Scattering Theory. Springer (2013)Google Scholar
- 10.Cakoni, F., Colton, D., Monk, P.: The Linear Sampling Method in Inverse Electromagnetic Scattering. SIAM-Society for Industrial and Applied Mathematics (2010)Google Scholar
- 16.Gabriel, S., Lau, R.W., Gabriel, C.: The dielectric properties of biological tissues: III. parametric models for the dielectric spectrum of tissues. Phys. Med. Biology 41(11), 2271–2293 (1996)Google Scholar
- 17.Guzina, B.B., Cakoni, F., Bellis, C.: On the multi-frequency obstacle reconstruction via the linear sampling method. Inverse Prob. 26(12), 125,005 (2010)Google Scholar
- 20.Kirsch, A., Grinberg, N.: The Factorization Method for Inverse Problems, 1 edn. Oxford University Press (2008)Google Scholar
- 21.Kress, R.: Linear Integral Equations, 3 edn. Springer (2013)Google Scholar
- 23.Mobashsher, A.T., Mahmoud, A., Abbosh, A.M.: Portable wideband microwave imaging system for intracranial hemorrhage detection using improved back-projection algorithm with model of effective head permittivity. Sci. Rep. 6, 20,459 (2016)Google Scholar
- 31.Scapaticci, R., Crocco, L., Bucci, O.M., Catapano, I.: Assessment of inversion strategies for microwave imaging of weak magnetic scatterers embedded into a biological environment. In: 2012 6th European Conference on Antennas and Propagation (EUCAP). IEEE (2012)Google Scholar