Current medical imaging uses MRI or CT images to diagnose tissue injuries. In addition to this classic procedure, there are also alternative technologies that have advantages against MRI or CT. These include electrical impedance tomography (EIT). With the help of EIT it is possible to obtain an initial screening of the body quickly and without a lot of hardware. Classical software-based methods of imaging reconstruction use a linear back projection or iterative approaches, such as Gauss-Newton algorithm. This paper introduces innovative approaches of artificial intelligence (AI) for imaging. For this purpose, extensive AI-based simulations with a Generative Adversial Network (GAN) are performed and the approaches are transferred to a gelatine phantom and to the human body within a small study.
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