Zobrazeno 1 - 10
of 561
pro vyhledávání: '"Braren, Rickmer"'
Physics-inspired regularization is desired for intra-patient image registration since it can effectively capture the biomechanical characteristics of anatomical structures. However, a major challenge lies in the reliance on physical parameters: Param
Externí odkaz:
http://arxiv.org/abs/2407.04355
Autor:
Fischer, Maximilian, Neher, Peter, Wald, Tassilo, Almeida, Silvia Dias, Xiao, Shuhan, Schüffler, Peter, Braren, Rickmer, Götz, Michael, Muckenhuber, Alexander, Kleesiek, Jens, Nolden, Marco, Maier-Hein, Klaus
Processing histopathological Whole Slide Images (WSI) leads to massive storage requirements for clinics worldwide. Even after lossy image compression during image acquisition, additional lossy compression is frequently possible without substantially
Externí odkaz:
http://arxiv.org/abs/2406.12623
Autor:
Bujotzek, Markus R., Akünal, Ünal, Denner, Stefan, Neher, Peter, Zenk, Maximilian, Frodl, Eric, Jaiswal, Astha, Kim, Moon, Krekiehn, Nicolai R., Nickel, Manuel, Ruppel, Richard, Both, Marcus, Döllinger, Felix, Opitz, Marcel, Persigehl, Thorsten, Kleesiek, Jens, Penzkofer, Tobias, Maier-Hein, Klaus, Braren, Rickmer, Bucher, Andreas
Objective: Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments due to numerous hurdles impeding its translation into practice. The fe
Externí odkaz:
http://arxiv.org/abs/2405.09409
Autor:
Spieker, Veronika, Eichhorn, Hannah, Stelter, Jonathan K., Huang, Wenqi, Braren, Rickmer F., Rückert, Daniel, Costabal, Francisco Sahli, Hammernik, Kerstin, Prieto, Claudia, Karampinos, Dimitrios C., Schnabel, Julia A.
Neural implicit k-space representations have shown promising results for dynamic MRI at high temporal resolutions. Yet, their exclusive training in k-space limits the application of common image regularization methods to improve the final reconstruct
Externí odkaz:
http://arxiv.org/abs/2404.08350
Autor:
Ziller, Alexander, Mueller, Tamara T., Stieger, Simon, Feiner, Leonhard, Brandt, Johannes, Braren, Rickmer, Rueckert, Daniel, Kaissis, Georgios
Artificial Intelligence (AI) models are vulnerable to information leakage of their training data, which can be highly sensitive, for example in medical imaging. Privacy Enhancing Technologies (PETs), such as Differential Privacy (DP), aim to circumve
Externí odkaz:
http://arxiv.org/abs/2312.04590
Autor:
Feiner, Leonhard F., Menten, Martin J., Hammernik, Kerstin, Hager, Paul, Huang, Wenqi, Rueckert, Daniel, Braren, Rickmer F., Kaissis, Georgios
Uncertainty estimation, which provides a means of building explainable neural networks for medical imaging applications, have mostly been studied for single deep learning models that focus on a specific task. In this paper, we propose a method to pro
Externí odkaz:
http://arxiv.org/abs/2309.16831
Autor:
Dima, Alina F., Zimmer, Veronika A., Menten, Martin J., Li, Hongwei Bran, Graf, Markus, Lemke, Tristan, Raffler, Philipp, Graf, Robert, Kirschke, Jan S., Braren, Rickmer, Rueckert, Daniel
Automated segmentation of the blood vessels in 3D volumes is an essential step for the quantitative diagnosis and treatment of many vascular diseases. 3D vessel segmentation is being actively investigated in existing works, mostly in deep learning ap
Externí odkaz:
http://arxiv.org/abs/2309.08481
Autor:
Starck, Sophie, Sideri-Lampretsa, Vasiliki, Ritter, Jessica J. M., Zimmer, Veronika A., Braren, Rickmer, Mueller, Tamara T., Rueckert, Daniel
Population atlases are commonly utilised in medical imaging to facilitate the investigation of variability across populations. Such atlases enable the mapping of medical images into a common coordinate system, promoting comparability and enabling the
Externí odkaz:
http://arxiv.org/abs/2308.14365
Autor:
Spieker, Veronika, Huang, Wenqi, Eichhorn, Hannah, Stelter, Jonathan, Weiss, Kilian, Zimmer, Veronika A., Braren, Rickmer F., Karampinos, Dimitrios C., Hammernik, Kerstin, Schnabel, Julia A.
Motion-resolved reconstruction for abdominal magnetic resonance imaging (MRI) remains a challenge due to the trade-off between residual motion blurring caused by discretized motion states and undersampling artefacts. In this work, we propose to gener
Externí odkaz:
http://arxiv.org/abs/2308.08830
Autor:
Starck, Sophie, Kini, Yadunandan Vivekanand, Ritter, Jessica Johanna Maria, Braren, Rickmer, Rueckert, Daniel, Mueller, Tamara
Age prediction is an important part of medical assessments and research. It can aid in detecting diseases as well as abnormal ageing by highlighting the discrepancy between chronological and biological age. To gain a comprehensive understanding of ag
Externí odkaz:
http://arxiv.org/abs/2307.07439