Electrical impedance tomography (EIT) is a non-ionizing medical imaging technique in which electric fields are used to form images of organ function and structure. To form these images, it is necessary to solve a severely ill-posed inverse problem with computational efficiency. However, the ill-posedness compromises image resolution. Here, we present and compare several techniques in which a database of synthetic EIT data, formulated from a representative set of patient data, can be used to improve reconstructions, and still preserve the ability to produce real-time functional images. The effectiveness of the methods is demonstrated on simulated data and on data collected on patients of Children’s Hospital Colorado.
CAM / DoMSS Seminar
Monday, November 6
For those joining remotely, email Malena Espanol for the Zoom link.
Professor of Mathematics
Colorado State University