Self-supervised super-resolution for anisotropic MR images with and without slice gap

SW Remedios, S Han, L Zuo, A Carass… - … Workshop on Simulation …, 2023 - Springer
Magnetic resonance (MR) images are often acquired as multi-slice volumes to reduce scan
time and motion artifacts while improving signal-to-noise ratio. These slices often are thicker …

A deep learning framework for image super-resolution for late gadolinium enhanced cardiac MRI

RR Upendra, R Simon, CA Linte - 2021 Computing in …, 2021 - ieeexplore.ieee.org
Cardiac magnetic resonance imaging (MRI) provides 3D images with high-resolution in-
plane information, however, they are known to have low through-plane resolution due to the …

Deep learning architecture for 3D image super-resolution of late gadolinium enhanced cardiac MRI

RR Upendra, R Simon, CA Linte - Journal of Medical Imaging, 2023 - spiedigitallibrary.org
Purpose High-resolution late gadolinium enhanced (LGE) cardiac magnetic resonance
imaging (MRI) volumes are difficult to acquire due to the limitations of the maximal breath …

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DBG Super-Resolution - … , PRIME 2023, Held in Conjunction with …, 2023 - books.google.com
The super-resolution of low-resolution brain graphs, also known as brain connectomes, is a
crucial aspect of neuroimaging research, especially in brain graph super-resolution. Brain …

Self-supervised super-resolution of 2-D pre-clinical MRI acquisitions

L Guo, SW Remedios, A Korotcov… - Medical Imaging 2024 …, 2024 - spiedigitallibrary.org
Animal models are pivotal in disease research and the advancement of therapeutic
methods. The translation of results from these models to clinical applications is enhanced by …