Dominik Narnhofer

Dominik Narnhofer
Graz University of Technology | TU Graz · Institute for Computer Graphics and Vision

Master of Science

About

5
Publications
371
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57
Citations

Publications

Publications (5)
Article
Recent deep learning approaches focus on improving quantitative scores of dedicated benchmarks, and therefore only reduce the observation-related (aleatoric) uncertainty. However, the model-immanent (epistemic) uncertainty is less frequently systematically analyzed. In this work, we introduce a Bayesian variational framework to quantify the epistem...
Preprint
Recent deep learning approaches focus on improving quantitative scores of dedicated benchmarks, and therefore only reduce the observation-related (aleatoric) uncertainty. However, the model-immanent (epistemic) uncertainty is less frequently systematically analyzed. In this work, we introduce a Bayesian variational framework to quantify the epistem...
Conference Paper
In this work, fully automatic binary segmentation of GBMs (glioblastoma multiforme) in 2D magnetic resonance images is presented using a convolutional neural network trained exclusively on synthetic data. The precise segmentation of brain tumors is one of the most complex and challenging tasks in clinical practice and is usually done manually by ra...
Article
In the search for a novel MRI contrast agent which relies on T1 shortening due to quadrupolar interaction between Bi nuclei and protons, a fast scanning wideband system for zero-field nuclear quadrupole resonance (NQR) spectroscopy is required. Established NQR probeheads with motor-driven tune/match stages are usually bulky and slow, which can be p...

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