Deep learning approaches for data augmentation in medical imaging: a review
A Kebaili, J Lapuyade-Lahorgue, S Ruan - Journal of Imaging, 2023 - mdpi.com
Deep learning has become a popular tool for medical image analysis, but the limited
availability of training data remains a major challenge, particularly in the medical field where …
availability of training data remains a major challenge, particularly in the medical field where …
[HTML][HTML] A survey of emerging applications of diffusion probabilistic models in mri
Diffusion probabilistic models (DPMs) which employ explicit likelihood characterization and
a gradual sampling process to synthesize data, have gained increasing research interest …
a gradual sampling process to synthesize data, have gained increasing research interest …
Can segmentation models be trained with fully synthetically generated data?
In order to achieve good performance and generalisability, medical image segmentation
models should be trained on sizeable datasets with sufficient variability. Due to ethics and …
models should be trained on sizeable datasets with sufficient variability. Due to ethics and …
South Asian, Black and White ethnicity and the effect of potentially modifiable risk factors for dementia: A study in English electronic health records
Introduction We aimed to investigate ethnic differences in the associations of potentially
modifiable risk factors with dementia. Methods We used anonymised data from English …
modifiable risk factors with dementia. Methods We used anonymised data from English …
Circulating metabolome and white matter hyperintensities in women and men
Background: White matter hyperintensities (WMH), identified on T2-weighted magnetic
resonance images of the human brain as areas of enhanced brightness, are a major risk …
resonance images of the human brain as areas of enhanced brightness, are a major risk …
[HTML][HTML] Generating multi-pathological and multi-modal images and labels for brain MRI
The last few years have seen a boom in using generative models to augment real datasets,
as synthetic data can effectively model real data distributions and provide privacy …
as synthetic data can effectively model real data distributions and provide privacy …
Assessment of the impact of a personalised nutrition intervention in impaired glucose regulation over 26 weeks: a randomised controlled trial
M Karvela, CT Golden, N Bell, S Martin-Li… - Scientific Reports, 2024 - nature.com
Dietary interventions can reduce progression to type 2 diabetes mellitus (T2DM) in people
with non-diabetic hyperglycaemia. In this study we aimed to determine the impact of a DNA …
with non-diabetic hyperglycaemia. In this study we aimed to determine the impact of a DNA …
[HTML][HTML] Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts
RF Hillary, HK Ng, DL McCartney, HR Elliott… - Cell Genomics, 2024 - cell.com
Chronic inflammation is a hallmark of age-related disease states. The effectiveness of
inflammatory proteins including C-reactive protein (CRP) in assessing long-term …
inflammatory proteins including C-reactive protein (CRP) in assessing long-term …
Impact of afterload and infiltration on coexisting aortic stenosis and transthyretin amyloidosis
Objective The coexistence of wild-type transthyretin cardiac amyloidosis (ATTR) is common
in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve …
in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve …
Near-infrared spectroscopy (NIRS) in vivo assessment of skeletal muscle oxidative capacity: a comparison of results from short versus long exercise protocols and …
FJ Tandirerung, A Jamieson, E Hendrick… - Frontiers in …, 2024 - frontiersin.org
Background Near-infrared spectroscopy (NIRS) provides a non-invasive, cost-effective
method for assessing skeletal muscle oxidative capacity when combined with a short …
method for assessing skeletal muscle oxidative capacity when combined with a short …