1 citations · 1 across the 4 of their papers we have counts for
5 papers
Scale-Cascaded Diffusion Models for Super-Resolution in Medical Imaging
Darshan Thaker, Mahmoud Mostapha, Radu Miron +2
Diffusion models have been increasingly used as strong generative priors for solving inverse problems such as super-resolution in medical imaging. However, these approaches typical…
Investigating the Feasibility of Patch-based Inference for Generalized Diffusion Priors in Inverse Problems for Medical Images
Saikat Roy, Mahmoud Mostapha, Radu Miron +2
Plug-and-play approaches to solving inverse problems such as restoration and super-resolution have recently benefited from Diffusion-based generative priors for natural as well as…
Benchmarking 3D multi-coil NC-PDNet MRI reconstruction
Asma Tanabene, Chaithya Giliyar Radhakrishna, Aurélien Massire +2
Deep learning has shown great promise for MRI reconstruction from undersampled data, yet there is a lack of research on validating its performance in 3D parallel imaging acquisitio…
GFB-MRF: A parallel spatial and Bloch manifold regularized iterative reconstruction method for MR Fingerprinting
Simon Arberet, Xiao Chen, Boris Mailhe +5
Magnetic Resonance Fingerprinting (MRF) reconstructs tissue maps based on a sequence of very highly undersampled images. In order to be able to perform MRF reconstruction, state-of…
Brain Segmentation from k-space with End-to-end Recurrent Attention Network
Qiaoying Huang, Xiao Chen, Dimitris Metaxas +1
The task of medical image segmentation commonly involves an image reconstruction step to convert acquired raw data to images before any analysis. However, noises, artifacts and los…