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pro vyhledávání: '"BAUMGARTNER, Christian"'
Data scarcity is a major limiting factor for applying modern machine learning techniques to clinical tasks. Although sufficient data exists for some well-studied medical tasks, there remains a long tail of clinically relevant tasks with poor data ava
Externí odkaz:
http://arxiv.org/abs/2408.08058
Inverse problems, such as accelerated MRI reconstruction, are ill-posed and an infinite amount of possible and plausible solutions exist. This may not only lead to uncertainty in the reconstructed image but also in downstream tasks such as semantic s
Externí odkaz:
http://arxiv.org/abs/2407.18026
Autor:
Wundram, Anna M., Fischer, Paul, Muehlebach, Michael, Koch, Lisa M., Baumgartner, Christian F.
Recent works have introduced methods to estimate segmentation performance without ground truth, relying solely on neural network softmax outputs. These techniques hold potential for intuitive output quality control. However, such performance estimate
Externí odkaz:
http://arxiv.org/abs/2407.13307
Deformable image registration is fundamental to many medical imaging applications. Registration is an inherently ambiguous task often admitting many viable solutions. While neural network-based registration techniques enable fast and accurate registr
Externí odkaz:
http://arxiv.org/abs/2407.10567
Autor:
Fischer, Paul, Willms, Hannah, Schneider, Moritz, Thorwarth, Daniela, Muehlebach, Michael, Baumgartner, Christian F.
Cancer remains a leading cause of death, highlighting the importance of effective radiotherapy (RT). Magnetic resonance-guided linear accelerators (MR-Linacs) enable imaging during RT, allowing for inter-fraction, and perhaps even intra-fraction, adj
Externí odkaz:
http://arxiv.org/abs/2407.08432
Autor:
Reinhardt, Simon, Penner, Alexander-Georg, Berger, Johanna, Baumgartner, Christian, Gronin, Sergei, Gardner, Geoffrey C., Lindemann, Tyler, Manfra, Michael J., Glazman, Leonid I., von Oppen, Felix, Paradiso, Nicola, Strunk, Christoph
We demonstrate transport in 2D arrays of multiterminal $\varphi_0$-junctions. When applying an in-plane magnetic field we observe nonreciprocal vortex depinning currents, induced by a ratchet-like pinning potential. The ratchet effect is explained as
Externí odkaz:
http://arxiv.org/abs/2406.13819
Interpretability is crucial for machine learning algorithms in high-stakes medical applications. However, high-performing neural networks typically cannot explain their predictions. Post-hoc explanation methods provide a way to understand neural netw
Externí odkaz:
http://arxiv.org/abs/2406.05477
While the field of medical image analysis has undergone a transformative shift with the integration of machine learning techniques, the main challenge of these techniques is often the scarcity of large, diverse, and well-annotated datasets. Medical i
Externí odkaz:
http://arxiv.org/abs/2404.16000
Autor:
Baumgartner, Christian, Schaub, Michael Patrick, Wenger, Andreas, Malischnig, Doris, Augsburger, Mareike, Walter, Marc, Berger, Thomas, Stark, Lars, Ebert, David Daniel, Keough, Matthew T, Haug, Severin
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 4, p e27463 (2021)
BackgroundDespite increasing demand for treatment among cannabis users in many countries, most users are not in treatment. Internet-based self-help offers an alternative for those hesitant to seek face-to-face therapy, though low effectiveness and ad
Externí odkaz:
https://doaj.org/article/5d179130a67343e7a7ff429a6d9569c6
Early detection of anomalies in medical images such as brain MRI is highly relevant for diagnosis and treatment of many conditions. Supervised machine learning methods are limited to a small number of pathologies where there is good availability of l
Externí odkaz:
http://arxiv.org/abs/2312.01904