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15 February 2021 Simulation and evaluation of imaging for electrical impedance tomography using artificial intelligence methods
Author Affiliations +
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.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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KEYWORDS
Artificial intelligence

Tomography

Magnetic resonance imaging

Computed tomography

Reconstruction algorithms

Image restoration

Injuries

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