Zobrazeno 1 - 10
of 972
pro vyhledávání: '"Navarro, Fernando A."'
Autor:
Tölle, Malte, Navarro, Fernando, Eble, Sebastian, Wolf, Ivo, Menze, Bjoern, Engelhardt, Sandy
Federated learning is one popular paradigm to train a joint model in a distributed, privacy-preserving environment. But partial annotations pose an obstacle meaning that categories of labels are heterogeneous over clients. We propose to learn a joint
Externí odkaz:
http://arxiv.org/abs/2407.07488
Autor:
Li, Hongwei Bran, Navarro, Fernando, Ezhov, Ivan, Bayat, Amirhossein, Das, Dhritiman, Kofler, Florian, Shit, Suprosanna, Waldmannstetter, Diana, Paetzold, Johannes C., Hu, Xiaobin, Wiestler, Benedikt, Zimmer, Lucas, Amiranashvili, Tamaz, Prabhakar, Chinmay, Berger, Christoph, Weidner, Jonas, Alonso-Basant, Michelle, Rashid, Arif, Baid, Ujjwal, Adel, Wesam, Ali, Deniz, Baheti, Bhakti, Bai, Yingbin, Bhatt, Ishaan, Cetindag, Sabri Can, Chen, Wenting, Cheng, Li, Dutand, Prasad, Dular, Lara, Elattar, Mustafa A., Feng, Ming, Gao, Shengbo, Huisman, Henkjan, Hu, Weifeng, Innani, Shubham, Jiat, Wei, Karimi, Davood, Kuijf, Hugo J., Kwak, Jin Tae, Le, Hoang Long, Lia, Xiang, Lin, Huiyan, Liu, Tongliang, Ma, Jun, Ma, Kai, Ma, Ting, Oksuz, Ilkay, Holland, Robbie, Oliveira, Arlindo L., Pal, Jimut Bahan, Pei, Xuan, Qiao, Maoying, Saha, Anindo, Selvan, Raghavendra, Shen, Linlin, Silva, Joao Lourenco, Spiclin, Ziga, Talbar, Sanjay, Wang, Dadong, Wang, Wei, Wang, Xiong, Wang, Yin, Xia, Ruiling, Xu, Kele, Yan, Yanwu, Yergin, Mert, Yu, Shuang, Zeng, Lingxi, Zhang, YingLin, Zhao, Jiachen, Zheng, Yefeng, Zukovec, Martin, Do, Richard, Becker, Anton, Simpson, Amber, Konukoglu, Ender, Jakab, Andras, Bakas, Spyridon, Joskowicz, Leo, Menze, Bjoern
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentat
Externí odkaz:
http://arxiv.org/abs/2405.18435
Autor:
Yang, Kaiyuan, Musio, Fabio, Ma, Yihui, Juchler, Norman, Paetzold, Johannes C., Al-Maskari, Rami, Höher, Luciano, Li, Hongwei Bran, Hamamci, Ibrahim Ethem, Sekuboyina, Anjany, Shit, Suprosanna, Huang, Houjing, Prabhakar, Chinmay, de la Rosa, Ezequiel, Waldmannstetter, Diana, Kofler, Florian, Navarro, Fernando, Menten, Martin, Ezhov, Ivan, Rueckert, Daniel, Vos, Iris, Ruigrok, Ynte, Velthuis, Birgitta, Kuijf, Hugo, Hämmerli, Julien, Wurster, Catherine, Bijlenga, Philippe, Westphal, Laura, Bisschop, Jeroen, Colombo, Elisa, Baazaoui, Hakim, Makmur, Andrew, Hallinan, James, Wiestler, Bene, Kirschke, Jan S., Wiest, Roland, Montagnon, Emmanuel, Letourneau-Guillon, Laurent, Galdran, Adrian, Galati, Francesco, Falcetta, Daniele, Zuluaga, Maria A., Lin, Chaolong, Zhao, Haoran, Zhang, Zehan, Ra, Sinyoung, Hwang, Jongyun, Park, Hyunjin, Chen, Junqiang, Wodzinski, Marek, Müller, Henning, Shi, Pengcheng, Liu, Wei, Ma, Ting, Yalçin, Cansu, Hamadache, Rachika E., Salvi, Joaquim, Llado, Xavier, Estrada, Uma Maria Lal-Trehan, Abramova, Valeriia, Giancardo, Luca, Oliver, Arnau, Liu, Jialu, Huang, Haibin, Cui, Yue, Lin, Zehang, Liu, Yusheng, Zhu, Shunzhi, Patel, Tatsat R., Tutino, Vincent M., Orouskhani, Maysam, Wang, Huayu, Mossa-Basha, Mahmud, Zhu, Chengcheng, Rokuss, Maximilian R., Kirchhoff, Yannick, Disch, Nico, Holzschuh, Julius, Isensee, Fabian, Maier-Hein, Klaus, Sato, Yuki, Hirsch, Sven, Wegener, Susanne, Menze, Bjoern
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to affect the risk, severity, and clinical outcome of serious neuro-vascular diseases. However, character
Externí odkaz:
http://arxiv.org/abs/2312.17670
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2023)
Detection Transformers represent end-to-end object detection approaches based on a Transformer encoder-decoder architecture, exploiting the attention mechanism for global relation modeling. Although Detection Transformers deliver results on par with
Externí odkaz:
http://arxiv.org/abs/2207.10774
Autor:
Navarro, Fernando, Sasahara, Guido, Shit, Suprosanna, Ezhov, Ivan, Peeken, Jan C., Combs, Stephanie E., Menze, Bjoern H.
Automatic localization and segmentation of organs-at-risk (OAR) in CT are essential pre-processing steps in medical image analysis tasks, such as radiation therapy planning. For instance, the segmentation of OAR surrounding tumors enables the maximiz
Externí odkaz:
http://arxiv.org/abs/2203.00624
Autor:
Hernández-Guillén, David, García-Gomariz, Carmen, Roig-Casasús, Sergio, Díaz-Díaz, Beatriz, Domínguez-Navarro, Fernando, Pérez-Maletzki, José, Blasco, José-María
Publikováno v:
In International Journal of Osteopathic Medicine September 2024 53
Autor:
Peeken, Jan C., Etzel, Lucas, Tomov, Tim, Münch, Stefan, Schüttrumpf, Lars, Shaktour, Julius H., Kiechle, Johannes, Knebel, Carolin, Schaub, Stephanie K., Mayr, Nina A., Woodruff, Henry C., Lambin, Philippe, Gersing, Alexandra S., Bernhardt, Denise, Nyflot, Matthew J., Menze, Bjoern, Combs, Stephanie E., Navarro, Fernando
Publikováno v:
In Radiotherapy and Oncology August 2024 197
Autor:
Tetteh, Giles, Navarro, Fernando, Paetzold, Johannes, Kirschke, Jan, Zimmer, Claus, Menze, Bjoern H.
Collateral circulation results from specialized anastomotic channels which are capable of providing oxygenated blood to regions with compromised blood flow caused by ischemic injuries. The quality of collateral circulation has been established as a k
Externí odkaz:
http://arxiv.org/abs/2110.12508
Autor:
Cerrillo-Sanchis, Julia, Ricart-Luna, Borja, Rodrigo-Mallorca, Darío, Muñoz-Gómez, Elena, Domínguez-Navarro, Fernando, Mollà-Casanova, Sara, Chulvi-Medrano, Iván
Publikováno v:
In Journal of Bodywork & Movement Therapies July 2024 39:43-49
Autor:
Navarro, Fernando, Watanabe, Christopher, Shit, Suprosanna, Sekuboyina, Anjany, Peeken, Jan C., Combs, Stephanie E., Menze, Bjoern H.
Self-supervision has demonstrated to be an effective learning strategy when training target tasks on small annotated data-sets. While current research focuses on creating novel pretext tasks to learn meaningful and reusable representations for the ta
Externí odkaz:
http://arxiv.org/abs/2105.06986