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eess.IV2024
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data
Alexander Denker, Zeljko Kereta, Imraj Singh +4
Electrical impedance tomography (EIT) plays a crucial role in non-invasive imaging, with both medical and industrial applications. In this paper, we present three data-driven recon…
eess.IV2023★ 1 cited
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction
Marco Nittscher, Michael Lameter, Riccardo Barbano +3
The deep image prior (DIP) is a well-established unsupervised deep learning method for image reconstruction; yet it is far from being flawless. The DIP overfits to noise if not ear…