Zobrazeno 1 - 10
of 13 407
pro vyhledávání: '"Christian, F. A."'
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
Autor:
Rutherford, Saige, Wolfers, Thomas, Fraza, Charlotte, Harrnet, Nathaniel G., Beckmann, Christian F., Ruhe, Henricus G., Marquand, Andre F.
Reference classes in healthcare establish healthy norms, such as pediatric growth charts of height and weight, and are used to chart deviations from these norms which represent potential clinical risk. How the demographics of the reference class infl
Externí odkaz:
http://arxiv.org/abs/2407.19114
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:
Zollicoffer, Geigh, Bhatta, Kshitij, Bhattarai, Manish, Romero, Phil, Negre, Christian F. A., Niklasson, Anders M. N., Adedoyin, Adetokunbo
In this paper, we introduce innovative approaches for accelerating the Jacobi method for matrix diagonalization, specifically through the formulation of large matrix diagonalization as a Semi-Markov Decision Process and small matrix diagonalization a
Externí odkaz:
http://arxiv.org/abs/2407.00779
Autor:
Bhatta, Kshitij, Zollicoffer, Geigh, Bhattarai, Manish, Romero, Phil, Negre, Christian F. A., Niklasson, Anders M. N., Adedoyin, Adetokunbo
This paper introduces a novel framework for matrix diagonalization, recasting it as a sequential decision-making problem and applying the power of Decision Transformers (DTs). Our approach determines optimal pivot selection during diagonalization wit
Externí odkaz:
http://arxiv.org/abs/2406.16191
Autor:
Schmidt, Christian F., Parra-López, Álvaro, Tolosa-Simeón, Mireia, Sparn, Marius, Kath, Elinor, Liebster, Nikolas, Duchene, Jelte, Strobel, Helmut, Oberthaler, Markus K., Floerchinger, Stefan
The production of quantum field excitations or particles in cosmological spacetimes is a hallmark prediction of curved quantum field theory. The generation of cosmological perturbations from quantum fluctuations in the early universe constitutes an i
Externí odkaz:
http://arxiv.org/abs/2406.08094
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