
Does contextual information improve 3D UNet based brain tumor segmentation?
Effective, robust and automatic tools for brain tumor segmentation are n...
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What is the best data augmentation approach for brain tumor segmentation using 3D UNet?
Training segmentation networks requires large annotated datasets, which ...
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Synthesizing brain tumor images and annotations by combining progressive growing GAN and SPADE
Training segmentation networks requires large annotated datasets, but ma...
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Feeding the zombies: Synthesizing brain volumes using a 3D progressive growing GAN
Deep learning requires large datasets for training (convolutional) netwo...
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Anatomically informed Bayesian spatial priors for fMRI analysis
Existing Bayesian spatial priors for functional magnetic resonance imagi...
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Generating fMRI volumes from T1weighted volumes using 3D CycleGAN
Registration between an fMRI volume and a T1weighted volume is challeng...
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Spatial 3D Matérn priors for fast wholebrain fMRI analysis
Bayesian wholebrain functional magnetic resonance imaging (fMRI) analys...
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Graph Spectral Characterization of Brain Cortical Morphology
The human brain cortical layer has a convoluted morphology that is uniqu...
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Characterization of Brain Cortical Morphology Using Localized TopologyEncoding Graphs
The human brain cortical layer has a convoluted morphology that is uniqu...
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Refacing: reconstructing anonymized facial features using GANs
Anonymization of medical images is necessary for protecting the identity...
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Generating Diffusion MRI scalar maps from T1 weighted images using generative adversarial networks
Diffusion magnetic resonance imaging (diffusion MRI) is a noninvasive m...
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Reply to Chen et al.: Parametric methods for cluster inference perform worse for twosided ttests
Onesided ttests are commonly used in the neuroimaging field, but twos...
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Generative Adversarial Networks for ImagetoImage Translation on MultiContrast MR Images  A Comparison of CycleGAN and UNIT
In medical imaging, a general problem is that it is costly and time cons...
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Cluster Failure Revisited: Impact of First Level Design and Data Quality on Cluster False Positive Rates
Methodological research rarely generates a broad interest, yet our work ...
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Bayesian uncertainty quantification in linear models for diffusion MRI
Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue micr...
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Gaussian process regression can turn nonuniform and undersampled diffusion MRI data into diffusion spectrum imaging
We propose to use Gaussian process regression to accurately estimate the...
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Anders Eklund
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