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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.uni-trier.de./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
- 2024
[c7]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- [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
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