% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Zenk:279520,
author = {Zenk, Maximilian and Baid, Ujjwal and Pati, Sarthak and
Linardos, Akis and Edwards, Brandon and Sheller, Micah and
Foley, Patrick and Aristizabal, Alejandro and Zimmerer,
David and Gruzdev, Alexey and Martin, Jason and Shinohara,
Russell T and Reinke, Annika and Isensee, Fabian and
Parampottupadam, Santhosh and Parekh, Kaushal and Floca,
Ralf and Kassem, Hasan and Baheti, Bhakti and Thakur,
Siddhesh and Chung, Verena and Kushibar, Kaisar and Lekadir,
Karim and Jiang, Meirui and Yin, Youtan and Yang, Hongzheng
and Liu, Quande and Chen, Cheng and Dou, Qi and Heng,
Pheng-Ann and Zhang, Xiaofan and Zhang, Shaoting and Khan,
Muhammad Irfan and Azeem, Mohammad Ayyaz and Jafaritadi,
Mojtaba and Alhoniemi, Esa and Kontio, Elina and Khan,
Suleiman A and Mächler, Leon and Ezhov, Ivan and Kofler,
Florian and Shit, Suprosanna and Paetzold, Johannes C and
Loehr, Timo and Wiestler, Benedikt and Peiris, Himashi and
Pawar, Kamlesh and Zhong, Shenjun and Chen, Zhaolin and
Hayat, Munawar and Egan, Gary and Harandi, Mehrtash and Isik
Polat, Ece and Polat, Gorkem and Kocyigit, Altan and
Temizel, Alptekin and Tuladhar, Anup and Tyagi, Lakshay and
Souza, Raissa and Forkert, Nils D and Mouches, Pauline and
Wilms, Matthias and Shambhat, Vishruth and Maurya, Akansh
and Danannavar, Shubham Subhas and Kalla, Rohit and Anand,
Vikas Kumar and Krishnamurthi, Ganapathy and Nalawade, Sahil
and Ganesh, Chandan and Wagner, Ben and Reddy, Divya and
Das, Yudhajit and Yu, Fang F and Fei, Baowei and
Madhuranthakam, Ananth J and Maldjian, Joseph and Singh,
Gaurav and Ren, Jianxun and Zhang, Wei and An, Ning and Hu,
Qingyu and Zhang, Youjia and Zhou, Ying and Siomos, Vasilis
and Tarroni, Giacomo and Passerrat-Palmbach, Jonathan and
Rawat, Ambrish and Zizzo, Giulio and Kadhe, Swanand Ravindra
and Epperlein, Jonathan P and Braghin, Stefano and Wang,
Yuan and Kanagavelu, Renuga and Wei, Qingsong and Yang,
Yechao and Liu, Yong and Kotowski, Krzysztof and Adamski,
Szymon and Machura, Bartosz and Malara, Wojciech and
Zarudzki, Lukasz and Nalepa, Jakub and Shi, Yaying and Gao,
Hongjian and Avestimehr, Salman and Yan, Yonghong and Akbar,
Agus S and Kondrateva, Ekaterina and Yang, Hua and Li,
Zhaopei and Wu, Hung-Yu and Roth, Johannes and Saueressig,
Camillo and Milesi, Alexandre and Nguyen, Quoc D and
Gruenhagen, Nathan J and Huang, Tsung-Ming and Ma, Jun and
Singh, Har Shwinder H and Pan, Nai-Yu and Zhang, Dingwen and
Zeineldin, Ramy A and Futrega, Michal and Yuan, Yading and
Conte, Gian Marco and Feng, Xue and Pham, Quan D and Xia,
Yong and Jiang, Zhifan and Luu, Huan Minh and Dobko, Mariia
and Carré, Alexandre and Tuchinov, Bair and Mohy-Ud-Din,
Hassan and Alam, Saruar and Singh, Anup and Shah, Nameeta
and Wang, Weichung and Sako, Chiharu and Bilello, Michel and
Ghodasara, Satyam and Mohan, Suyash and Davatzikos, Christos
and Calabrese, Evan and Rudie, Jeffrey and Villanueva-Meyer,
Javier and Cha, Soonmee and Hess, Christopher and Mongan,
John and Ingalhalikar, Madhura and Jadhav, Manali and
Pandey, Umang and Saini, Jitender and Huang, Raymond Y and
Chang, Ken and To, Minh-Son and Bhardwaj, Sargam and Chong,
Chee and Agzarian, Marc and Kozubek, Michal and Lux, Filip
and Michálek, Jan and Matula, Petr and Ker Kovský, Miloš
and Kopr Ivová, Tereza and Dostál, Marek and Vybíhal,
Václav and Pinho, Marco C and Holcomb, James and Metz,
Marie and Jain, Rajan and Lee, Matthew D and Lui, Yvonne W
and Tiwari, Pallavi and Verma, Ruchika and Bareja, Rohan and
Yadav, Ipsa and Chen, Jonathan and Kumar, Neeraj and Gusev,
Yuriy and Bhuvaneshwar, Krithika and Sayah, Anousheh and
Bencheqroun, Camelia and Belouali, Anas and Madhavan, Subha
and Colen, Rivka R and Kotrotsou, Aikaterini and Vollmuth,
Philipp and Brugnara, Gianluca and Preetha, Chandrakanth J
and Sahm, Felix and Bendszus, Martin and Wick, Wolfgang and
Mahajan, Abhishek and Balaña, Carmen and Capellades, Jaume
and Puig, Josep and Choi, Yoon Seong and Lee, Seung-Koo and
Chang, Jong Hee and Ahn, Sung Soo and Shaykh, Hassan F and
Herrera-Trujillo, Alejandro and Trujillo, Maria and Escobar,
William and Abello, Ana and Bernal, Jose and Gómez, Jhon
and LaMontagne, Pamela and Marcus, Daniel S and Milchenko,
Mikhail and Nazeri, Arash and Landman, Bennett and Ramadass,
Karthik and Xu, Kaiwen and Chotai, Silky and Chambless, Lola
B and Mistry, Akshitkumar and Thompson, Reid C and
Srinivasan, Ashok and Bapuraj, J Rajiv and Rao, Arvind and
Wang, Nicholas and Yoshiaki, Ota and Moritani, Toshio and
Turk, Sevcan and Lee, Joonsang and Prabhudesai, Snehal and
Garrett, John and Larson, Matthew and Jeraj, Robert and Li,
Hongwei and Weiss, Tobias and Weller, Michael and Bink,
Andrea and Pouymayou, Bertrand and Sharma, Sonam and Tseng,
Tzu-Chi and Adabi, Saba and Xavier Falcão, Alexandre and
Martins, Samuel B and Teixeira, Bernardo C A and Sprenger,
Flávia and Menotti, David and Lucio, Diego R and Niclou,
Simone P and Keunen, Olivier and Hau, Ann-Christin and
Pelaez, Enrique and Franco-Maldonado, Heydy and Loayza,
Francis and Quevedo, Sebastian and McKinley, Richard and
Slotboom, Johannes and Radojewski, Piotr and Meier, Raphael
and Wiest, Roland and Trenkler, Johannes and Pichler, Josef
and Necker, Georg and Haunschmidt, Andreas and Meckel,
Stephan and Guevara, Pamela and Torche, Esteban and Mendoza,
Cristobal and Vera, Franco and Ríos, Elvis and López,
Eduardo and Velastin, Sergio A and Choi, Joseph and Baek,
Stephen and Kim, Yusung and Ismael, Heba and Allen, Bryan
and Buatti, John M and Zampakis, Peter and Panagiotopoulos,
Vasileios and Tsiganos, Panagiotis and Alexiou, Sotiris and
Haliassos, Ilias and Zacharaki, Evangelia I and Moustakas,
Konstantinos and Kalogeropoulou, Christina and Kardamakis,
Dimitrios M and Luo, Bing and Poisson, Laila M and Wen, Ning
and Vallières, Martin and Loutfi, Mahdi Ait Lhaj and
Fortin, David and Lepage, Martin and Morón, Fanny and
Mandel, Jacob and Shukla, Gaurav and Liem, Spencer and
Alexandre, Gregory S and Lombardo, Joseph and Palmer, Joshua
D and Flanders, Adam E and Dicker, Adam P and Ogbole, Godwin
and Oyekunle, Dotun and Odafe-Oyibotha, Olubunmi and Osobu,
Babatunde and Shu'aibu Hikima, Mustapha and Soneye, Mayowa
and Dako, Farouk and Dorcas, Adeleye and Murcia, Derrick and
Fu, Eric and Haas, Rourke and Thompson, John A and Ormond,
David Ryan and Currie, Stuart and Fatania, Kavi and Frood,
Russell and Simpson, Amber L and Peoples, Jacob J and Hu,
Ricky and Cutler, Danielle and Moraes, Fabio Y and Tran, Anh
and Hamghalam, Mohammad and Boss, Michael A and Gimpel,
James and Kattil Veettil, Deepak and Schmidt, Kendall and
Cimino, Lisa and Price, Cynthia and Bialecki, Brian and
Marella, Sailaja and Apgar, Charles and Jakab, Andras and
Weber, Marc-André and Colak, Errol and Kleesiek, Jens and
Freymann, John B and Kirby, Justin S and Maier-Hein, Lena
and Albrecht, Jake and Mattson, Peter and Karargyris,
Alexandros and Shah, Prashant and Menze, Bjoern and
Maier-Hein, Klaus and Bakas, Spyridon},
title = {{T}owards fair decentralized benchmarking of healthcare
{AI} algorithms with the {F}ederated {T}umor {S}egmentation
({F}e{TS}) challenge.},
journal = {Nature Communications},
volume = {16},
number = {1},
issn = {2041-1723},
address = {[London]},
publisher = {Springer Nature},
reportid = {DZNE-2025-00843},
pages = {6274},
year = {2025},
abstract = {Computational competitions are the standard for
benchmarking medical image analysis algorithms, but they
typically use small curated test datasets acquired at a few
centers, leaving a gap to the reality of diverse
multicentric patient data. To this end, the Federated Tumor
Segmentation (FeTS) Challenge represents the paradigm for
real-world algorithmic performance evaluation. The FeTS
challenge is a competition to benchmark (i) federated
learning aggregation algorithms and (ii) state-of-the-art
segmentation algorithms, across multiple international
sites. Weight aggregation and client selection techniques
were compared using a multicentric brain tumor dataset in
realistic federated learning simulations, yielding benefits
for adaptive weight aggregation, and efficiency gains
through client sampling. Quantitative performance evaluation
of state-of-the-art segmentation algorithms on data
distributed internationally across 32 institutions yielded
good generalization on average, albeit the worst-case
performance revealed data-specific modes of failure. Similar
multi-site setups can help validate the real-world utility
of healthcare AI algorithms in the future.},
keywords = {Humans / Benchmarking: methods / Algorithms / Brain
Neoplasms: diagnostic imaging / Image Processing,
Computer-Assisted: methods / Artificial Intelligence /
Magnetic Resonance Imaging},
cin = {AG Düzel},
ddc = {500},
cid = {I:(DE-2719)5000006},
pnm = {353 - Clinical and Health Care Research (POF4-353)},
pid = {G:(DE-HGF)POF4-353},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:40628696},
doi = {10.1038/s41467-025-60466-1},
url = {https://pub.dzne.de/record/279520},
}
guest ::