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Daniel Truhn

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Zunamys I. Carrero

> Home > Persons > Daniel Truhn

Publications

2026
[j22]
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  - journals/bmcmi/MiseraNCBLKHTK26
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Leo Misera, Sven Nebelung, Zunamys I. Carrero, Keno K. Bressem, Marta Ligero, Jens-Peter Kühn, Ralf-Thorsten Hoffmann, Daniel Truhn, Jakob Nikolas Kather:
Reducing manual workload in CT and MRI annotation with the Segment Anything Model 2. BMC Medical Imaging 26(1): 54 (2026)
[j21]
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  - journals/braininf/JuglanLCMLMVKKNTK26
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Radhika Juglan, Marta Ligero, Zunamys I. Carrero, Asier Rabasco Meneghetti, Tim Lenz, Leo Misera, Gregory Patrick Veldhuizen, Paul Kuntke, Hagen H. Kitzler, Sven Nebelung, Daniel Truhn, Jakob Nikolas Kather:
Generalizable and explainable deep learning for brain MRI: a multi-cohort evaluation of 3D architectures for age and sex prediction. Brain Informatics 13(1): 31 (2026)
2025
[i52]
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  - journals/corr/abs-2506-23916
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Radhika Juglan, Marta Ligero, Zunamys I. Carrero, Asier Rabasco Meneghetti, Tim Lenz, Leo Misera, Gregory Patrick Veldhuizen, Paul Kuntke, Hagen H. Kitzler, Sven Nebelung, Daniel Truhn, Jakob Nikolas Kather:
Three-dimensional end-to-end deep learning for brain MRI analysis. CoRR abs/2506.23916 (2025)
2024
[j8]
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  - journals/npjdm/WiestFZTMJCPKETK24
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Isabella C. Wiest, Dyke Ferber, Jiefu Zhu, Marko van Treeck, Sonja K. Meyer, Radhika Juglan, Zunamys I. Carrero, Daniel Paech, Jens Kleesiek, Matthias P. Ebert, Daniel Truhn, Jakob Nikolas Kather:
Privacy-preserving large language models for structured medical information retrieval. npj Digit. Medicine 7(1) (2024)
[c23]
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  - conf/eccv/WolfleinFMNTCHAK24
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Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelovic, Jakob Nikolas Kather:
A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification. ECCV Workshops (16) 2024: 68-87
2023
[i13]
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  - journals/corr/abs-2311-11772
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Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelovic, Jakob Nikolas Kather:
A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology. CoRR abs/2311.11772 (2023)

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