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20172024
most citedLow-field magnetic resonance image enhancement via stochastic image quality transfer

42 citations · 58 across the 10 of their papers we have counts for

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5 papers · 1 filter

eess.IV2024

MRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels

Moucheng Xu, Yukun Zhou, Tobias Goodwin-Allcock +4

We introduce and demonstrate a new paradigm for quantitative parameter mapping in MRI. Parameter mapping techniques, such as diffusion MRI and quantitative MRI, have the potential…

eess.IV20242 cited

Alternative Learning Paradigms for Image Quality Transfer

Ahmed Karam Eldaly, Matteo Figini, Daniel C. Alexander

Image Quality Transfer (IQT) aims to enhance the contrast and resolution of low-quality medical images, e.g. obtained from low-power devices, with rich information learned from hig…

eess.IV20233 cited

A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI

Seunghoi Kim, Henry F. J. Tregidgo, Ahmed K. Eldaly +2

Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution…

eess.IV202342 cited

Low-field magnetic resonance image enhancement via stochastic image quality transfer

Hongxiang Lin, Matteo Figini, Felice D'Arco +10

Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher…

eess.IV2022

Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors

Shahab Aslani, Watjana Lilaonitkul, Vaishnavi Gnanananthan +7

During the COVID-19 pandemic, the sheer volume of imaging performed in an emergency setting for COVID-19 diagnosis has resulted in a wide variability of clinical CXR acquisitions.…