7 papers
What is the best data augmentation for 3D brain tumor segmentation?
Marco Domenico Cirillo, David Abramian, Anders Eklund
Training segmentation networks requires large annotated datasets, which in medical imaging can be hard to obtain. Despite this fact, data augmentation has in our opinion not been f…
Vox2Vox: 3D-GAN for Brain Tumour Segmentation
Marco Domenico Cirillo, David Abramian, Anders Eklund
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histological sub-regions, i.e., perit…
Improved functional MRI activation mapping in white matter through diffusion-adapted spatial filtering
David Abramian, Martin Larsson, Anders Eklund +1
Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD con…
Anatomically informed Bayesian spatial priors for fMRI analysis
David Abramian, Per Sidén, Hans Knutsson +2
Existing Bayesian spatial priors for functional magnetic resonance imaging (fMRI) data correspond to stationary isotropic smoothing filters that may oversmooth at anatomical bounda…
Structural mediation of human brain activity revealed by white-matter interpolation of fMRI
Anjali Tarun, Hamid Behjat, David Abramian +1
Anatomy of the human brain constrains the formation of large-scale functional networks. Here, given measured brain activity in gray matter, we interpolate these functional signals…
Generating fMRI volumes from T1-weighted volumes using 3D CycleGAN
David Abramian, Anders Eklund
Registration between an fMRI volume and a T1-weighted volume is challenging, since fMRI volumes contain geometric distortions. Here we present preliminary results showing that 3D C…