University of Cambridge > Talks.cam > Cambridge Image Analysis Seminars > Data-driven enhancement of electrical impedance tomography using segmentation flow

Data-driven enhancement of electrical impedance tomography using segmentation flow

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If you have a question about this talk, please contact Carola-Bibiane Schoenlieb.

Electrical Impedance Tomography (EIT) is a non-invasive, inexpensive, and portable medical imaging modality where the patient is probed with electric currents fed through electrodes positioned on the skin. The resulting voltages at the electrodes are measured, and the goal is to recover the internal electric conductivity of the body. The reconstruction task is a highly ill-posed nonlinear inverse problem and requires the use of regularized solution methods. In the so-called D-bar method, one uses a nonlinear low-pass filter to provide regularization. However, this results in a blurry reconstruction that obscures crisp boundaries between tissues. We propose sharpening the EIT image using the diffusive image segmentation of Ambrosio and Tortorelli, controlled by the EIT data vie the so-called CGO sinogram.

This talk is part of the Cambridge Image Analysis Seminars series.

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