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ORCIDDaniel Lang 0003
Person information
- affiliation: Helmholtz Center Munich, Institute of Machine Learning in Biomedical Imaging, Germany
- affiliation: Technical University of Munich, School of Computation, Information and Technology, Germany
Other persons with the same name
- Daniel Lang — disambiguation page
- Daniel Lang 0001
![[0000-0002-2166-0716]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-2166-0716")
— University of Freiburg, Faculty of Biology, Freiburg Initiative in Systems Biology, FRISYS, Germany - Daniel Lang 0002 — SMART, Telecom Ecole de Mangement, TEM, DSI, Evry, France
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2020 – today
- 2026
[j3]Nicholas Konz, Richard Osuala, Preeti Verma, Yuwen Chen, Hanxue Gu, Haoyu Dong, Yaqian Chen, Andrew Marshall, Lidia Garrucho, Kaisar Kushibar, Daniel Lang, Sungheon Gene Kim, Lars J. Grimm, John Lewin, James S. Duncan, Julia A. Schnabel, Oliver Díaz, Karim Lekadir, Maciej A. Mazurowski:
Fréchet radiomic distance (FRD): A versatile metric for comparing medical imaging datasets. Medical Image Anal. 110: 103943 (2026)- [j2]Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang, Cosmin I. Bercea, Matthew Nyflot, Lina Felsner, Julia A. Schnabel, Jan C. Peeken:
TomoGraphView: 3D medical image classification with omnidirectional slice representations and graph neural networks. Medical Image Anal. 113: 104174 (2026) - [j1]Stefan M. Fischer, Johannes Kiechle, Laura Daza, Lina Felsner, Richard Osuala, Daniel Lang, Karim Lekadir, Jan C. Peeken, Julia A. Schnabel:
Progressive growing of patch size: Curriculum learning for accelerated and improved medical image segmentation. Medical Image Anal. 113: 104195 (2026) - [c12]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Abstract: Progressive Growing of Patch Size - Curriculum Learning for Accelerated, Improved Medical Image Segmentation. Bildverarbeitung für die Medizin 2026: 267-268 - [c11]Sameer Ambekar, Marta Hasny, Laura Daza, Daniel Lang, Julia A. Schnabel:
Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation. WACV 2026: 4661-4672 - [i17]Sameer Ambekar, Reza Nasirigerdeh, Peter J. Schuffler, Lina Felsner, Daniel Lang, Julia A. Schnabel:
The Mean is the Mirage: Entropy-Adaptive Model Merging under Heterogeneous Domain Shifts in Medical Imaging. CoRR abs/2602.21372 (2026) - [i16]Tim Nielen, Sameer Ambekar, Johannes Kiechle, Daniel M. Lang, Julia A. Schnabel:
Entropy Minimization without Model Collapse: Mitigating Prediction Bias in Medical Imaging. CoRR abs/2606.02339 (2026) - [i15]Johannes Kiechle, Richard Osuala, Daniel M. Lang, Stefan M. Fischer, Ivana Janícková, Karim Lekadir, Julia A. Schnabel, Jan C. Peeken:
Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction. CoRR abs/2607.04912 (2026) - [i14]Smriti Joshi, Apostolia Tsirikoglou, Daniel Lang, Richard Osuala, Noah Márquez Varaa, Alejandro Guzmán, Grzegorz Skorupko, Sebastian Ibarra Arregui, Lidia Garrucho, Akane Ohashi, Dimitra Ntoula, Eugen Divjak, Oguz Lafci, Jan C. Peeken, Julia A. Schnabel, Fredrik Strand, Oliver Díaz, Karim Lekadir:
Dense Temporal Contrast Synthesis via Conditioned Latent Transport. CoRR abs/2607.29394 (2026) - 2025
- [c10]Daniel Lang, Richard Osuala, Veronika Spieker, Karim Lekadir, Rickmer Braren, Julia A. Schnabel:
Temporal Neural Cellular Automata: Application to Modeling of Contrast Enhancement in Breast MRI. MICCAI (4) 2025: 604-614 - [i13]Daniel M. Lang, Richard Osuala, Veronika Spieker, Karim Lekadir, Rickmer Braren, Julia A. Schnabel:
Temporal Neural Cellular Automata: Application to modeling of contrast enhancement in breast MRI. CoRR abs/2506.18720 (2025) - [i12]Sameer Ambekar, Daniel M. Lang, Julia A. Schnabel:
Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation. CoRR abs/2508.09223 (2025) - [i11]Stefan M. Fischer, Johannes Kiechle, Laura Daza, Lina Felsner, Richard Osuala, Daniel M. Lang, Karim Lekadir, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Curriculum Learning for Accelerated and Improved Medical Image Segmentation. CoRR abs/2510.23241 (2025) - [i10]Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang, Cosmin I. Bercea, Matthew Nyflot, Lina Felsner, Julia A. Schnabel, Jan C. Peeken:
TomoGraphView: 3D Medical Image Classification with Omnidirectional Slice Representations and Graph Neural Networks. CoRR abs/2511.09605 (2025) - [i9]Xingyu Zhang, Anna Reithmeir, Fryderyk Victor Kögl, Rickmer Braren, Julia A. Schnabel, Daniel M. Lang:
MedDIFT: Multi-Scale Diffusion-Based Correspondence in 3D Medical Imaging. CoRR abs/2512.05571 (2025) - 2024
- [c9]Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang, Maxime Di Folco, Sarah C. Foreman, Verena K. N. Rösner, Ann-Kathrin Lohse, Carolin Mogler, Carolin Knebel, Marcus R. Makowski, Klaus Woertler, Stephanie E. Combs, Alexandra S. Gersing, Jan C. Peeken, Julia A. Schnabel:
Unifying Local and Global Shape Descriptors to Grade Soft-Tissue Sarcomas Using Graph Convolutional Networks. ISBI 2024: 1-5 - [c8]Johannes Kiechle, Daniel Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel:
Graph Neural Networks: A Suitable Alternative to MLPs in Latent 3D Medical Image Classification? GRAIL@MICCAI 2024: 12-22 - [c7]Richard Osuala, Daniel Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Enhancing the Utility of Privacy-Preserving Cancer Classification Using Synthetic Data. Deep-Breath@MICCAI 2024: 54-64 - [c6]Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
MedEdit: Counterfactual Diffusion-Based Image Editing on Brain MRI. SASHIMI@MICCAI 2024: 167-176 - [c5]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. MICCAI (9) 2024: 510-520 - [c4]Richard Osuala, Daniel M. Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Towards Learning Contrast Kinetics with Multi-condition Latent Diffusion Models. MICCAI (5) 2024: 713-723 - [i8]Richard Osuala, Daniel Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models. CoRR abs/2403.13890 (2024) - [i7]Stefan M. Fischer, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge. CoRR abs/2406.14365 (2024) - [i6]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. CoRR abs/2407.07853 (2024) - [i5]Richard Osuala, Daniel M. Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data. CoRR abs/2407.12669 (2024) - [i4]Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI. CoRR abs/2407.15270 (2024) - [i3]Johannes Kiechle, Daniel M. Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel:
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification? CoRR abs/2407.17219 (2024) - [i2]Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, Lidia Garrucho, Walter H. L. Pinaya, Daniel M. Lang, Julia A. Schnabel, Oliver Díaz, Karim Lekadir:
Simulating Dynamic Tumor Contrast Enhancement in Breast MRI using Conditional Generative Adversarial Networks. CoRR abs/2409.18872 (2024) - 2023
- [c3]Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel:
Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI. CaPTion@MICCAI 2023: 55-67 - 2021
- [c2]Daniel M. Lang, Jan C. Peeken, Stephanie E. Combs, Jan J. Wilkens, Stefan Bartzsch:
A Video Data Based Transfer Learning Approach for Classification of MGMT Status in Brain Tumor MR Images. BrainLes@MICCAI (1) 2021: 306-314 - [c1]Daniel M. Lang, Jan C. Peeken, Stephanie E. Combs, Jan J. Wilkens, Stefan Bartzsch:
Deep Learning Based GTV Delineation and Progression Free Survival Risk Score Prediction for Head and Neck Cancer Patients. HECKTOR@MICCAI 2021: 150-159 - 2020
- [i1]Daniel M. Lang, Jan C. Peeken, Stephanie E. Combs, Jan J. Wilkens, Stefan Bartzsch:
Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients. CoRR abs/2011.08555 (2020)
Coauthor Index
aka: Jan C. Peeken
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