Using real data to train GREIT improves image quality
نویسندگان
چکیده
Image reconstruction in electrical impedance tomography is sensitive to errors in the (forward) model of the measurement system. We propose a new approach, based on the GREIT algorithm, where the reconstruction matrix is trained on real rather than simulated data, obviating the need for an accurate numerical forward model. We observe a substantial improvement in image quality, particularly for changes close to the boundary.
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تاریخ انتشار 2014