Lin Yang

TL;DR: The results showed that the impedance spectra of stroke lesions significantly differed from those of normal brain tissue; the ratio of change in impedance of ischemic and hemorrhagic tissue with regard to frequency was distinct; and tissue type could be discriminated according to its impedance specta.

TL;DR: The results showed that the contact impedance at high frequencies significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images.

TL;DR: A spectral decomposition frequency-difference imaging algorithm is presented that is capable of detecting the anomaly in a numerical head phantom, as well as in a realistic human head tank with frequency-dependent and heterogeneous conductivities distribution.

TL;DR: The results demonstrated that the impedance spectra differed significantly between healthy and stroke-affected brain (i.e., hemorrhagic or ischemic brain), and validated the feasibility of using MFEIT to detect stroke and differentiate stroke types.

TL;DR: A framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes is developed and a novel algorithm, called SB-IBCD, is compared with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity.