3 papers
cs.CV2026
Principled Design of Diffusion-based Optimizers for Inverse Problems
Julio Oscanoa, Irmak Sivgin, Cagan Alkan +4
Score-based diffusion models achieve state-of-the-art performance for inverse problems, but their practical deployment is hindered by long inference times and cumbersome hyperparam…
eess.IV2024
On the Foundation Model for Cardiac MRI Reconstruction
Chi Zhang, Michael Loecher, Cagan Alkan +3
In recent years, machine learning (ML) based reconstruction has been widely investigated and employed in cardiac magnetic resonance (CMR) imaging. ML-based reconstructions can deli…
eess.SP2024
Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies
Jiahao Huang, Yinzhe Wu, Fanwen Wang +17
Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric…