Hugging Face Trending Papers
Jun 25

Enabling self-supervised learned primal dual with Noise2Inverse

X-ray computed tomography reconstruction is an ill-posed inverse problem, particularly in low-dose and sparse-angle settings where measurements are noisy and incomplete. While learned reconstruction methods such as the Learned Primal-Dual algorithm achieve strong performance, they typically rely on supervised training with access to ground-truth data, which is often unavailable in practice.

arXiv Machine Learning
Jun 26

Enabling self-supervised learned primal dual with Noise2Inverse

arXiv:2606. 26991v1 Announce Type: cross Abstract: X-ray computed tomography reconstruction is an ill-posed inverse problem, particularly in low-dose and sparse-angle settings where measurements are noisy and incomplete.

By Antti S\"allinen, Siiri Rautio, Santeri Kaupinm\"aki, Andreas Hauptmann