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A study on correlation between structure and resistivity variations was performed for live adult human skull. The resistivities of 388 skull samples, excised from 48 skull flaps of patients undergoing surgery, were measured at body temperature (36.5[degrees]C) using the well-known four-electrode method in the frequency range of 1-4 MHz. According to different structures of the skull samples, all the 388 samples were classified into six categories and measured their resistivities: standard trilayer skull (7943 [+ or -] 1752 [ohms] x cm, 58 samples), quasi-trilayer skull (14471 [+ or -] 3061 [ohms] x cm, 110 samples), standard compact skull (26546 [+ or -] 5374 [ohms] x cm, 62 samples), quasi-compact skull (19824 [+ or -] 3232 [ohms] x cm, 53 samples), dentate suture skull (5782 [+ or -] 1778 [ohms] x cm, 41 samples), and squamous suture skull (12747 [+ or -] 4120 [ohms] x cm, 64 samples). The results showed that the skull resistivities were not homogenous and were significantly influenced by local structural variations. The presence of sutures appeared to decrease the overall resistivity of particular regions largely and dentate suture decreased the resistivity more than squamous suture. The absence of diploe appeared to increase skull resistivity. The percentage on thickness of diploe would be the primary factor in determining the resistivity of the skull sample without suture. From resistivity spectra results, an inverse relationship between skull resistivity and signal frequency was found. Index Terms--Diploe, resistivity, skull, structure, suture.

In electrical impedance tomography, currents are applied to the body through electrodes that are attached to the surface and the corresponding surface voltages are measured. Based on these boundary measurements, the internal admittivity distribution of the body can be reconstructed. In order to improve the image quality it is necessary and useful to apply physiologically meaningful prior information into the image reconstruction. Such prior information usually can be obtained from other sources. For example, information on the object's boundary shape and internal structure can be obtained from computed tomography and magnetic resonance imaging scan. However, this type of prior information may change from time to time and from person to person. As these changes are limited anatomically and physiologically, the prior information including the possible changes can be presented in a number of variational forms. The aim of this paper is to find which form of prior information is more compatible for a specific imaged object at the time of imaging. This paper proposes a new method for selecting the most appropriate form of prior information, through the procedure of iterative image reconstruction by using the information obtained from boundary measurements. The method is based on the principle that incompatible prior information causes errors which are able to affect the image reconstruction's convergence behavior. In this method, according to the various forms of prior information available, several image reconstruction configurations are designed. Then, through monitoring the convergence behavior in an iterative image reconstruction, the configuration with compatible prior information can be found among those different configurations. As an example, the prior information regarding the imaged object's boundary shape and internal structure was studied by computer simulation. Results were shown and discussed. Index Terms--Compatible, electrical impedance tomography, image reconstruction, imaging, prior information.

We proposed a new method based on total relative change (TRC) from measured boundary voltages to quantify the volume changes of fluid during electrical impedance tomography (EIT) monitoring. The results showed that TRC linearly correlated with the volume of infused saline solution into a phantom, and the slope of TRC changes was approximately linear with the infusion speed. A inserted copper tube at different positions did not affect TRC significantly. The linear relationship between TRC and volume change indicates that TRC could be a good quantitative index for dynamic EIT. Index Terms--Electrical impedance tomography, quantification, total relative change.

Background: Electrode disconnection is a common occurrence during long-term monitoring of brain electrical impedance tomography (EIT) in clinical settings. The data acquisition system suffers remarkable data loss which results in image reconstruction failure. The aim of this study was to: (1) detect disconnected electrodes and (2) account for invalid data.Methods: Weighted correlation coefficient for each electrode was calculated based on the measurement differences between well-connected and disconnected electrodes. Disconnected electrodes were identified by filtering out abnormal coefficients with discrete wavelet transforms. Further, previously valid measurements were utilized to establish grey model. The invalid frames after electrode disconnection were substituted with the data estimated by grey model. The proposed approach was evaluated on resistor phantom and with eight patients in clinical settings.Results: The proposed method was able to detect 1 or 2 disconnected electrodes with an accuracy of 100%; to detect 3 and 4 disconnected electrodes with accuracy of 92 and 84% respectively. The time cost of electrode detection was within 0.018 s. Further, the proposed method was capable to compensate at least 60 subsequent frames of data and restore the normal image reconstruction within 0.4 s and with a mean relative error smaller than 0.01%.Conclusions: In this paper, we proposed a two-step approach to detect multiple disconnected electrodes and to compensate the invalid frames of data after disconnection. Our method is capable of detecting more disconnected electrodes with higher accuracy compared to methods proposed in previous studies. Further, our method provides estimations during the faulty measurement period until the medical staff reconnects the electrodes. This work would improve the clinical practicability of dynamic brain EIT and contribute to its further promotion. [ABSTRACT FROM AUTHOR]

Stroke has a high mortality and disability rate and should be rapidly diagnosed to improve prognosis. Diagnosing stroke is not a problem for hospitals with CT, MRI, and other imaging devices but is difficult for community hospitals without these devices. Based on the mechanism that the electrical impedance of the two hemispheres of a normal human head is basically symmetrical and a stroke can alter this symmetry, a fast electrical impedance imaging method called symmetrical electrical impedance tomography (SEIT) is proposed. In this technique, electrical impedance tomography (EIT) data measured from the undamaged craniocerebral hemisphere (CCH) is regarded as reference data for the remaining EIT data measured from the other CCH for difference imaging to identify the differences in resistivity distribution between the two CCHs. The results of SEIT imaging based on simulation data from the 2D human head finite element model and that from the physical phantom of human head verified this method in detection of unilateral stroke.