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Efficient brain age prediction from 3D MRI volumes using 2D projections
Johan Jönemo, Muhammad Usman Akbar, Robin Kämpe +2
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. Here we d…
Does an ensemble of GANs lead to better performance when training segmentation networks with synthetic images?
Måns Larsson, Muhammad Usman Akbar, Anders Eklund
Large annotated datasets are required to train segmentation networks. In medical imaging, it is often difficult, time consuming and expensive to create such datasets, and it may al…
NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification
Shreyas Fadnavis, Jens Sjölund, Anders Eklund +1
Diffusion MRI (dMRI) is the only non-invasive technique sensitive to tissue micro-architecture, which can, in turn, be used to reconstruct tissue microstructure and white matter pa…
Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images
Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini
In the application of deep learning on optical coherence tomography (OCT) data, it is common to train classification networks using 2D images originating from volumetric data. Give…