# Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications
## 5 EIT Clinical-Based Applications
### Head Imaging  
Brain imaging is a challenging clinical task. The brain tissues impedance increases drastically during cerebral ischemia. To calculate the severity of the stroke a non-invasive technique is required. [PERSON] has performed different experiments with both cranial and intracranial electrodes on anesthetized rats [79] and obtained images of cerebral ischemia. He carried out a research review on EIT. By using electrodes, he stated that the visible surface of the cerebral cortex of the animals is very effective over milliseconds associated to neuronal depolarization in imaging evoked impedance variations and over a number of seconds for those linked to metabolic recovery procedures. The deviations have been observed during evoked responses and cortical spreading depression [80]. He believed that in the near future the process would be used for brain imaging for humans too. For static imaging of the head, the authors have developed, studied and compared three EIT techniques. Based on the real head model for impedance reconstruction of the head section, they applied these techniques to a 2D model. The results validated that the amalgam of the improved Newton-Raphson, and differential evolution algorithms have better performance in imaging quality, less computational time and are vigorous. The authors have also presented the particle swarm optimization algorithm for reconstructing the brain EIT images. Outcomes showed the error measures are limited within the define limits even under noisy conditions and the system is stable. They concluded that this PSO-EIT technique could be used in neurophysiological studies and to measure head geometry [15]. For head phantoms for intracranial hemorrhage (ICH) an EIT method is used to identify and image impedance variations. With and without a craniotomy, the authors have modeled the head phantoms of ICH. They have made two accurate head-shape models and a non-uniform resistivity distribution for brain EIT. To the head phantoms, they have inserted animal blood to replicate the ICH procedure and observed electrical impedance variations in real time with EIT. They have concluded from the injection of the blood region in one head phantom without the craniotomy that a growing impedance area appeared and on the other hand, in the second head phantom a reduced impedance area appeared. This shows that EIT is sensitive to impedance variations due to blood change. Instead, between two head phantoms, the varying trend showed in a contrasting way. This effect might be due to the variations in intracranial space and intracranial pressure. Therefore, for the treatment of ICH and for early diagnosis, EIT can be used. To solve the EIT inverse problem a differential evolution (DE) algorithm can be used [66]. For the forward problem, a FEM is chosen to determine the cost function. For real head model, this technique is applied for the 2D impedance reconstruction of brain section. Results showed that for the EIT problems the differential evolution algorithm is good in performance for obtaining high-quality reconstruction. [PERSON] et al. [81] have reconstructed the real head model to examine the EIT images for the head. They have observed that because the skull forms a physical barrier and restricts the current flow it is the basic issue for the reconstruction of the head impedance image. Image distortion is produced due to this low conductivity region where conductivity variations are localized towards the image center. Because of deficient spatial resolution, simple global variations are identified and due to this reason, the purpose of imaging cannot be achieved. The electrodes were placed directly on to the heads of some animals instead of using scalp electrodes. This approach measures the clear impedance variations associated with neuronal activity, but this technique is not practical in medical applications for human beings. Nevertheless, if those restrictions are solved the outcomes are promising if image reconstruction and data acquisition methods are improved.