2 citations · 2 across the 4 of their papers we have counts for
5 papers
Data-Efficient Networks for Multi-Contrast MRI Reconstruction based on a Generalized Content/Style Prior
Chinmay Rao, Efe Ilıcak, Matthias J. P. van Osch +5
Multi-contrast MR scans contain redundant structural information that can be leveraged during reconstruction and potentially accelerate acquisition times. This idea has inspired en…
Physics-Informed Deep Unrolled Network for Portable MR Image Reconstruction
Efe Ilıcak, Chinmay Rao, Chloé Najac +6
Magnetic resonance imaging (MRI) is the gold standard imaging modality for numerous diagnostic tasks, yet its usefulness is tempered due to its high cost and infrastructural requir…
UPCMR: A Universal Prompt-guided Model for Random Sampling Cardiac MRI Reconstruction
Donghang Lyu, Chinmay Rao, Marius Staring +4
Cardiac magnetic resonance imaging (CMR) is vital for diagnosing heart diseases, but long scan time remains a major drawback. To address this, accelerated imaging techniques have b…
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation
Prerak Mody, Nicolas F. Chaves-de-Plaza, Chinmay Rao +5
Increased usage of automated tools like deep learning in medical image segmentation has alleviated the bottleneck of manual contouring. This has shifted manual labour to quality as…
A Plug-and-Play Method for Guided Multi-contrast MRI Reconstruction based on Content/Style Modeling
Chinmay Rao, Matthias van Osch, Nicola Pezzotti +8
Since the various MR contrasts of a given anatomy contain redundant information, one contrast can be used to guide the reconstruction of another undersampled contrast acquired subs…