Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Effland, Alexander"'
Autor:
Haas, Manuel, Grandits, Thomas, Pinetz, Thomas, Beiert, Thomas, Pezzuto, Simone, Effland, Alexander
Reconstructing cardiac electrical activity from body surface electric potential measurements results in the severely ill-posed inverse problem in electrocardiography. Many different regularization approaches have been proposed to improve numerical re
Externí odkaz:
http://arxiv.org/abs/2408.11573
Autor:
Pinetz, Thomas, Kobler, Erich, Haase, Robert, Luetkens, Julian A., Meetschen, Mathias, Haubold, Johannes, Deuschl, Cornelius, Radbruch, Alexander, Deike, Katerina, Effland, Alexander
Recently, deep learning (DL)-based methods have been proposed for the computational reduction of gadolinium-based contrast agents (GBCAs) to mitigate adverse side effects while preserving diagnostic value. Currently, the two main challenges for these
Externí odkaz:
http://arxiv.org/abs/2403.03539
Autor:
Verhülsdonk, Jan, Grandits, Thomas, Costabal, Francisco Sahli, Pinetz, Thomas, Krause, Rolf, Auricchio, Angelo, Haase, Gundolf, Pezzuto, Simone, Effland, Alexander
The efficient construction of anatomical models is one of the major challenges of patient-specific in-silico models of the human heart. Current methods frequently rely on linear statistical models, allowing no advanced topological changes, or requiri
Externí odkaz:
http://arxiv.org/abs/2308.16568
The eikonal equation has become an indispensable tool for modeling cardiac electrical activation accurately and efficiently. In principle, by matching clinically recorded and eikonal-based electrocardiograms (ECGs), it is possible to build patient-sp
Externí odkaz:
http://arxiv.org/abs/2308.08410
Autor:
Pinetz, Thomas, Kobler, Erich, Haase, Robert, Deike-Hofmann, Katerina, Radbruch, Alexander, Effland, Alexander
Today Gadolinium-based contrast agents (GBCA) are indispensable in Magnetic Resonance Imaging (MRI) for diagnosing various diseases. However, GBCAs are expensive and may accumulate in patients with potential side effects, thus dose-reduction is recom
Externí odkaz:
http://arxiv.org/abs/2306.14678
The total generalized variation extends the total variation by incorporating higher-order smoothness. Thus, it can also suffer from similar discretization issues related to isotropy. Inspired by the success of novel discretization schemes of the tota
Externí odkaz:
http://arxiv.org/abs/2303.09349
Autor:
Grandits, Thomas, Effland, Alexander, Pock, Thomas, Krause, Rolf, Plank, Gernot, Pezzuto, Simone
The identification of the initial ventricular activation sequence is a critical step for the correct personalization of patient-specific cardiac models. In healthy conditions, the Purkinje network is the main source of the electrical activation, but
Externí odkaz:
http://arxiv.org/abs/2102.09962
Autor:
Narnhofer, Dominik, Effland, Alexander, Kobler, Erich, Hammernik, Kerstin, Knoll, Florian, Pock, Thomas
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 systemat
Externí odkaz:
http://arxiv.org/abs/2102.06665
We propose a novel learning-based framework for image reconstruction particularly designed for training without ground truth data, which has three major building blocks: energy-based learning, a patch-based Wasserstein loss functional, and shared pri
Externí odkaz:
http://arxiv.org/abs/2011.06539
Various problems in computer vision and medical imaging can be cast as inverse problems. A frequent method for solving inverse problems is the variational approach, which amounts to minimizing an energy composed of a data fidelity term and a regulari
Externí odkaz:
http://arxiv.org/abs/2006.08789