• Zhang, Tingting (Department Of Computational Science And Engineering, Yonsei University) ;
  • Bera, Tushar Kanti (Department Of Computational Science And Engineering, Yonsei University) ;
  • Woo, Eung Je (Department Of Biomedical Engineering, Kyung Hee University) ;
  • Seo, Jin Keun (Department Of Computational Science And Engineering, Yonsei University)
  • Received : 2014.04.19
  • Accepted : 2014.05.20
  • Published : 2014.06.25


Medical imaging techniques have evolved to expand our ability to visualize new contrast information of electrical, optical, and mechanical properties of tissues in the human body using noninvasive measurement methods. In particular, electrical tissue property imaging techniques have received considerable attention for the last few decades since electrical properties of biological tissues and organs change with their physiological functions and pathological states. We can express the electrical tissue properties as the frequency-dependent admittivity, which can be measured in a macroscopic scale by assessing the relation between the time-harmonic electric field and current density. The main issue is to reconstruct spectroscopic admittivity images from 10 Hz to 1 MHz, for example, with reasonably high spatial and temporal resolutions. It requires a solution of a nonlinear inverse problem involving Maxwell's equations. To solve the inverse problem with practical significance, we need deep knowledge on its mathematical formulation of underlying physical phenomena, implementation of image reconstruction algorithms, and practical limitations associated with the measurement sensitivity, specificity, noise, and data acquisition time. This paper discusses a number of issues in electrical tissue property imaging modalities and their future directions.


Supported by : National Research Foundation of Korea (NRF)


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