Low-resolution Prior Equilibrium Network for CT Reconstruction

arXiv:2401.15663v2 Announce Type: replace-cross
Abstract: The unrolling method has been investigated for learning variational models in X-ray computed tomography. However, it has been observed that directly unrolling the regularization model through gradient descent does not produce satisfactory results. In this paper, we present a novel deep learning-based CT reconstruction model, where the low-resolution image is introduced to obtain an effective regularization term for improving the network`s robustness. Our approach involves constructing the backbone network architecture by algorithm unrolling that is …

abstract arxiv cs.cv deep learning eess.iv equilibrium gradient however low network novel paper prior ray regularization resolution results through type x-ray x-ray computed tomography