Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Bujotzek, Markus"'
Autor:
Denner, Stefan, Bujotzek, Markus, Bounias, Dimitrios, Zimmerer, David, Stock, Raphael, Jäger, Paul F., Maier-Hein, Klaus
Medical image classification in radiology faces significant challenges, particularly in generalizing to unseen pathologies. In contrast, CLIP offers a promising solution by leveraging multimodal learning to improve zero-shot classification performanc
Externí odkaz:
http://arxiv.org/abs/2408.15802
Autor:
Schmidt, Kendall, Bearce, Benjamin, Chang, Ken, Coombs, Laura, Farahani, Keyvan, Elbatele, Marawan, Mouhebe, Kaouther, Marti, Robert, Zhang, Ruipeng, Zhang, Yao, Wang, Yanfeng, Hu, Yaojun, Ying, Haochao, Xu, Yuyang, Testagrose, Conrad, Demirer, Mutlu, Gupta, Vikash, Akünal, Ünal, Bujotzek, Markus, Maier-Hein, Klaus H., Qin, Yi, Li, Xiaomeng, Kalpathy-Cramer, Jayashree, Roth, Holger R.
Publikováno v:
Medical Image Analysis Volume 95, July 2024, 103206
The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due to the differences in imaging characteristics across mammography system
Externí odkaz:
http://arxiv.org/abs/2405.14900
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:
Denner, Stefan, Zimmerer, David, Bounias, Dimitrios, Bujotzek, Markus, Xiao, Shuhan, Kausch, Lisa, Schader, Philipp, Penzkofer, Tobias, Jäger, Paul F., Maier-Hein, Klaus
Content-based image retrieval (CBIR) has the potential to significantly improve diagnostic aid and medical research in radiology. Current CBIR systems face limitations due to their specialization to certain pathologies, limiting their utility. In res
Externí odkaz:
http://arxiv.org/abs/2403.06567
Autor:
Denner, Stefan, Scherer, Jonas, Kades, Klaus, Bounias, Dimitrios, Schader, Philipp, Kausch, Lisa, Bujotzek, Markus, Bucher, Andreas Michael, Penzkofer, Tobias, Maier-Hein, Klaus
In the rapidly evolving field of medical imaging, machine learning algorithms have become indispensable for enhancing diagnostic accuracy. However, the effectiveness of these algorithms is contingent upon the availability and organization of high-qua
Externí odkaz:
http://arxiv.org/abs/2309.17285
Publikováno v:
2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)
2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)
ISBN:978-1-4799-7528-0
ISBN:978-1-4799-7525-9
ISBN:978-1-4799-7528-0
ISBN:978-1-4799-7525-9
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b47cffed58f31451e621173568575be
https://hdl.handle.net/20.500.11850/90906
https://hdl.handle.net/20.500.11850/90906
Publikováno v:
IEEE Transactions on Power Delivery. Oct2014, Vol. 29 Issue 4, p1806-1813. 8p.
Publikováno v:
IEEE Transactions on Dielectrics & Electrical Insulation; Dec2016, Vol. 23 Issue 6, pii-iv, 3p
Autor:
Binod Bhattarai, Sharib Ali, Anita Rau, Anh Nguyen, Ana Namburete, Razvan Caramalau, Danail Stoyanov
Volume LNCS 14414 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada in October 2023.The DEMI 2023 proceedings c