Conditioning Generative Latent Optimization for Sparse-View CT Image Reconstruction

arXiv:2307.16670v3 Announce Type: replace
Abstract: Computed Tomography (CT) is a prominent example of Imaging Inverse Problem highlighting the unrivaled performances of data-driven methods in degraded measurements setups like sparse X-ray projections. Although a significant proportion of deep learning approaches benefit from large supervised datasets, they cannot generalize to new experimental setups. In contrast, fully unsupervised techniques, most notably using score-based generative models, have recently demonstrated similar or better performances compared to supervised approaches while being flexible at test time. However, …

abstract arxiv benefit cs.cv data data-driven datasets deep learning eess.iv example experimental generative highlighting image imaging optimization performances ray type view x-ray