5 citations · 10 across the 4 of their papers we have counts for
4 papers
Synthesizing brain tumor images and annotations by combining progressive growing GAN and SPADE
Mehdi Foroozandeh, Anders Eklund
Training segmentation networks requires large annotated datasets, but manual annotation is time consuming and costly. We here investigate if the combination of a noise-to-image GAN…
Feeding the zombies: Synthesizing brain volumes using a 3D progressive growing GAN
Anders Eklund
Deep learning requires large datasets for training (convolutional) networks with millions of parameters. In neuroimaging, there are few open datasets with more than 100 subjects, w…
A defense of using resting state fMRI as null data for estimating false positive rates
Thomas E. Nichols, Anders Eklund, Hans Knutsson
A recent Editorial by Slotnick (2017) reconsiders the findings of our paper on the accuracy of false positive rate control with cluster inference in fMRI (Eklund et al, 2016), in p…
Bayesian Non-Central Chi Regression For Neuroimaging
Bertil Wegmann, Anders Eklund, Mattias Villani
We propose a regression model for non-central (NC-) distributed functional magnetic resonance imaging (fMRI) and diffusion weighted imaging (DWI) data, with the heteroscedas…