Simulation and evaluation of imaging for electrical impedance tomography using artificial intelligence methods

Christian Gibas; Jonas Pöhler; Rainer Brück; Kristof Van Laerhoven

doi:10.1117/12.2581735

15 February 2021 Simulation and evaluation of imaging for electrical impedance tomography using artificial intelligence methods

Christian Gibas, Jonas Pöhler, Rainer Brück, Kristof Van Laerhoven

Author Affiliations +

Proceedings Volume 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging; 116001S (2021) https://doi.org/10.1117/12.2581735
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

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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Christian Gibas, Jonas Pöhler, Rainer Brück, and Kristof Van Laerhoven "Simulation and evaluation of imaging for electrical impedance tomography using artificial intelligence methods", Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 116001S (15 February 2021); https://doi.org/10.1117/12.2581735

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