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Maximilian Zenk
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2020 – today
- 2024
- [c8]Constantin Ulrich, Fabian Isensee, Tassilo Wald, Maximilian Zenk, Michael Baumgartner, Klaus H. Maier-Hein:
Abstract: Multi-dataset Approach to Medical Image Segmentation - MultiTalent. Bildverarbeitung für die Medizin 2024: 78 - [c7]Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk, Klaus H. Maier-Hein, Paul F. Jaeger:
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation. ICLR 2024 - [c6]Constantin Ulrich, Catherine Knobloch, Julius Holzschuh, Tassilo Wald, Maximilian R. Rokuss, Maximilian Zenk, Maximilian Fischer, Michael Baumgartner, Fabian Isensee, Klaus H. Maier-Hein:
Mitigating False Predictions in Unreasonable Body Regions. MLMI@MICCAI (2) 2024: 22-31 - [i10]Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk, Klaus H. Maier-Hein, Paul F. Jaeger:
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation. CoRR abs/2401.08501 (2024) - [i9]Yannick Kirchhoff, Maximilian R. Rokuss, Saikat Roy, Balint Kovacs, Constantin Ulrich, Tassilo Wald, Maximilian Zenk, Philipp Vollmuth, Jens Kleesiek, Fabian Isensee, Klaus H. Maier-Hein:
Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures. CoRR abs/2404.03010 (2024) - [i8]Constantin Ulrich, Catherine Knobloch, Julius Holzschuh, Tassilo Wald, Maximilian R. Rokuss, Maximilian Zenk, Maximilian Fischer, Michael Baumgartner, Fabian Isensee, Klaus H. Maier-Hein:
Mitigating False Predictions In Unreasonable Body Regions. CoRR abs/2404.15718 (2024) - [i7]Markus R. Bujotzek, Ünal Akünal, Stefan Denner, Peter Neher, Maximilian Zenk, Eric Frodl, Astha Jaiswal, Moon S. Kim, Nicolai R. Krekiehn, Manuel Nickel, Richard Ruppel, Marcus Both, Felix Döllinger, Marcel Opitz, Thorsten Persigehl, Jens Kleesiek, Tobias Penzkofer, Klaus H. Maier-Hein, Rickmer Braren, Andreas Bucher:
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain. CoRR abs/2405.09409 (2024) - [i6]Maximilian Zenk, David Zimmerer, Fabian Isensee, Jeremias Traub, Tobias Norajitra, Paul F. Jäger, Klaus H. Maier-Hein:
Comparative Benchmarking of Failure Detection Methods in Medical Image Segmentation: Unveiling the Role of Confidence Aggregation. CoRR abs/2406.03323 (2024) - [i5]Maximilian R. Rokuss, Yannick Kirchhoff, Saikat Roy, Balint Kovacs, Constantin Ulrich, Tassilo Wald, Maximilian Zenk, Stefan Denner, Fabian Isensee, Philipp Vollmuth, Jens Kleesiek, Klaus H. Maier-Hein:
Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting. CoRR abs/2409.13416 (2024) - 2023
- [j1]Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson:
Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. 5(7): 799-810 (2023) - [c5]Klaus Kades, Jonas Scherer, Maximilian Zenk, Marius Kempf, Klaus H. Maier-Hein:
Abstract: Towards Real-world Federated Learning in Medical Image Analysis using Kaapana. Bildverarbeitung für die Medizin 2023: 140 - [c4]Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, S. Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein:
Why is the Winner the Best? CVPR 2023: 19955-19966 - [c3]Constantin Ulrich, Fabian Isensee, Tassilo Wald, Maximilian Zenk, Michael Baumgartner, Klaus H. Maier-Hein:
MultiTalent: A Multi-dataset Approach to Medical Image Segmentation. MICCAI (3) 2023: 648-658 - [e2]Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, Reuben Dorent:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13769, Springer 2023, ISBN 978-3-031-33841-0 [contents] - [e1]Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, Reuben Dorent:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II. Lecture Notes in Computer Science 14092, Springer 2023, ISBN 978-3-031-44152-3 [contents] - [i4]Constantin Ulrich, Fabian Isensee, Tassilo Wald, Maximilian Zenk, Michael Baumgartner, Klaus H. Maier-Hein:
MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation. CoRR abs/2303.14444 (2023) - 2022
- [c2]Maximilian Zenk, David Zimmerer, Fabian Isensee, Paul F. Jäger, Jakob Wasserthal, Klaus H. Maier-Hein:
Realistic Evaluation of FixMatch on Imbalanced Medical Image Classification Tasks. Bildverarbeitung für die Medizin 2022: 291-296 - [c1]Klaus Kades, Jonas Scherer, Maximilian Zenk, Marius Kempf, Klaus H. Maier-Hein:
Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana. DeCaF/FAIR@MICCAI 2022: 130-140 - [i3]Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah J. Sheller, Hans Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus H. Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey D. Rudie, Javier E. Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña Quintero, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, et al.:
Federated Learning Enables Big Data for Rare Cancer Boundary Detection. CoRR abs/2204.10836 (2022) - 2021
- [i2]Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah J. Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Hassan M. Fathallah-Shaykh, Roland Wiest, András Jakab, Marc-André Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern H. Menze, Klaus H. Maier-Hein, Spyridon Bakas:
The Federated Tumor Segmentation (FeTS) Challenge. CoRR abs/2105.05874 (2021) - 2020
- [i1]Yang He, Maximilian Zenk, Mario Fritz:
CosSGD: Nonlinear Quantization for Communication-efficient Federated Learning. CoRR abs/2012.08241 (2020)
Coauthor Index
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last updated on 2024-10-31 20:18 CET by the dblp team
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