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Found 6 papers, 4 papers with code
Generalized super-resolution 4D Flow MRI $\unicode{x2013}$ using ensemble learning to extend across the cardiovascular system
4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system.
Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion models
Our results show that segmentation networks trained on synthetic images reach Dice scores that are 80% - 90% of Dice scores when training with real images, but that memorization of the training images can be a problem for diffusion models if the original dataset is too small.
Beware of diffusion models for synthesizing medical images -- A comparison with GANs in terms of memorizing brain MRI and chest x-ray images
Diffusion models were initially developed for text-to-image generation and are now being utilized to generate high-quality synthetic images.
Efficient brain age prediction from 3D MRI volumes using 2D projections
Using 3D CNNs on high resolution medical volumes is very computationally demanding, especially for large datasets like the UK Biobank which aims to scan 100, 000 subjects.
Does an ensemble of GANs lead to better performance when training segmentation networks with synthetic images?
Large annotated datasets are required to train segmentation networks.
AIforCOVID: predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study
Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, implying that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.
