Publications

2026

Li, K., Jaus, A., Kleesiek, J., & Stiefelhagen, R. (2026). GRASPing Anatomy to Improve Pathology Segmentation. In Z. Cui, I. Rekik, H.-I. Suk, X. Ouyang, K. Sun, & S. Wang, Machine Learning in Medical Imaging (S. 487–497). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-09513-8_47

Yamlahi, A., Kalinowski, P., Godau, P., Younis, R., Wagner, M., Müller, B., & Maier-Hein, L. (2026). Smarter Self-distillation: Optimizing the Teacher for Surgical Video Applications. In J. C. Gee, D. C. Alexander, J. Hong, J. E. Iglesias, C. H. Sudre, A. Venkataraman, P. Golland, J. H. Kim, & J. Park, Medical Image Computing and Computer Assisted Intervention – MICCAI 2025 (S. 522–531). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-05114-1_50

2025

Amaral, A. V. R., Wolffram, D., Moraga, P., & Bracher, J. (2025). Post-processing and weighted combination of infectious disease nowcasts. PLOS Computational Biology, 21(3), e1012836. https://doi.org/10.1371/journal.pcbi.1012836

Liu Y, Fransson P, Heidecke J, Liyanage P, Wallin J, Rocklöv J (2025) An explainable covariate compartmental model for predicting the spatio-temporal patterns of dengue in Sri Lanka. PLoS Comput Biol 21(9): e1013540. https://doi.org/10.1371/journal.pcbi.1013540

Baeuerle, S., Khanna, P., Friederich, N., Sitcheu, A. J. Y., Shakirov, D., Steimer, A., & Mikut, R. (2025). Are Foundation Models Ready for Industrial Defect Recognition? A Reality Check on Real-World Data. https://doi.org/10.48550/arXiv.2509.20479

Baumann, A., Ayala, L., Seidlitz, S., Sellner, J., Studier-Fischer, A., Özdemir, B., Maier-Hein, L., & Ilic, S. (2025). CARL: Camera-Agnostic Representation Learning for Spectral Image Analysis. https://doi.org/10.48550/arXiv.2504.19223

Beichter, M., Friederich, N., Pinter, J., Werling, D., Phipps, K., Beichter, S., Neumann, O., Mikut, R., Hagenmeyer, V., & Heidrich, B. (2025). Decision-focused fine-tuning of time series foundation models for dispatchable feeder optimization. Energy and AI, 21, 100533. https://doi.org/10.1016/j.egyai.2025.100533

Bitto, V., Jiang, X., Baumann, M., Kather, J. N., & Kurth, I. (2025). Deep Learning Predicts Survival Across Squamous Tumor Entities From H&E Stains: Insights from Head and Neck, Esophagus, Lung and Cervical Cancer (S. 2025.03.31.646351). https://doi.org/10.1101/2025.03.31.646351

Bitto, V., Jiang, X., Baumann, M., Kather, J. N., & Kurth, I. (2025). Deep Learning Predicts Survival Across Squamous Tumor Entities From Routine Pathology: Insights From Head and Neck, Esophagus, Lung, and Cervical Cancer. Modern Pathology, 38(12), 100845. https://doi.org/10.1016/j.modpat.2025.100845

Bouteille, L., Jaus, A., Kleesiek, J., Stiefelhagen, R., & Heine, L. (2025). Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation https://doi.org/10.48550/arXiv.2511.17146

Bracher, J., & Němcová, B. (2025). A unifying class of compound Poisson integer-valued ARMA and GARCH models. Scandinavian Journal of Statistics, 52(3), 1176–1205. https://doi.org/10.1111/sjos.12784

Caldarelli, P., Deininger, L., Zhao, S., Panda, P., Yang, C., Mikut, R., & Zernicka-Goetz, M. (2025). AI-based approach to dissect the variability of mouse stem cell-derived embryo models. Nature Communications, 16(1), 1772. https://doi.org/10.1038/s41467-025-56908-5

Ciolacu, G., Haas, C., & Hall, M. (2025). Rightsizing: Understanding Novice, Casual Learners of Programming. Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 2, 1421–1422. https://doi.org/10.1145/3641555.3705239

Disch, N. A., Kirchhoff, Y., Peretzke, R., Rokuss, M., Roy, S., Ulrich, C., Zimmerer, D., & Maier-Hein, K. (2025). Temporal Flow Matching for Learning Spatio-Temporal Trajectories in 4D Longitudinal Medical Imaging. https://doi.org/10.48550/arXiv.2508.21580

Disch, N. A., Roy, S., Ulrich, C., Kirchhoff, Y., Rokuss, M., Peretzke, R., Zimmerer, D., & Maier-Hein, K. (2025). CRONOS: Continuous Time Reconstruction for 4D Medical Longitudinal Series https://doi.org/10.48550/arXiv.2512.16577

Egen, L., Hommel, M., Haney, C. M., Özdemir, B., Knoedler, S., Sellner, J., Seidlitz, S., Dietrich, M., Salg, G. A., Nickel, F., Maier-Hein, L., Michel, M. S., Studier-Fischer, A., & Kowalewski, K.-F. (2025). Hyperspectral Imaging Accurately Detects Renal Malperfusion Due to High Intrarenal Pressure. European Urology Open Science, 78, 16–27. https://doi.org/10.1016/j.euros.2025.06.007

Fracarolli, M., Staniek, M., & Riezler, S. (2025). Embedding-Space Data Augmentation to Prevent Membership Inference Attacks in Clinical Time Series Forecasting. https://doi.org/10.48550/arXiv.2511.05289

Freymuth, N., Würth, T., Schreiber, N., Gyenes, B., Boltres, A., Mitsch, J., Taranovic, A., Hoang, T., Dahlinger, P., Becker, P., Kärger, L., & Neumann, G. (2025). AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction  https://doi.org/10.48550/arXiv.2505.23663

Friederich, N., Sitcheu, A. J. Y., Nassal, A., Yildiz, E., Pesch, M., Beichter, M., Scholtes, L., Akbaba, B., Lautenschlager, T., Neumann, O., Kohlheyer, D., Scharr, H., Seiffarth, J., Nöh, K., & Mikut, R. (2025). EAP4EMSIG – enhancing event-driven microscopy for microfluidic single-cell analysis:. At Automatisierungstechnik, 73(10), 808–823. https://doi.org/10.1515/auto-2025-0018

Godau, P., Kalinowski, P., Christodoulou, E., Reinke, A., Tizabi, M., Ferrer, L., Jäger, P., & Maier-Hein, L. (2025). Navigating prevalence shifts in image analysis algorithm deployment. Medical Image Analysis, 102, 103504. https://doi.org/10.1016/j.media.2025.103504

Gyenes, B., Franke, N., Scheikl, P. M., Henrich, P., Younis, R., Neumann, G., Wagner, M., & Mathis-Ullrich, F. (2025). Point Cloud Segmentation for Autonomous Clip Positioning in Laparoscopic Cholecystectomy on a Phantom. IEEE Robotics and Automation Letters, 10(8), 8522–8529. https://doi.org/10.1109/LRA.2025.3585357

Heinemann, L., Jaus, A., Marinov, Z., Kim, M., Spadea, M. F., Kleesiek, J., & Stiefelhagen, R. (2025). LIMIS: Towards Language-Based Interactive Medical Image Segmentation. 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 1–5. https://doi.org/10.1109/ISBI60581.2025.10981190

Herold, J., Brinkmeier, P., Götz, M., Schug, A., & Streit, A. (2025). Large-Scale Modeling of the Extracellular Matrix on Hybrid Supercomputers Using Highly Parallel Stencil Computations. ISC High Performance 2025 Research Paper Proceedings (40th International Conference), 1–14. https://doi.org/10.23919/ISC.2025.11017726

Jaus, A., Marinov, Z., Seibold, C., Reiß, S., Kleesiek, J., & Stiefelhagen, R. (2025). Good Enough: Is it Worth Improving your Label Quality? https://doi.org/10.48550/arXiv.2505.20928

Jaus, A., Seibold, C. M., Reiß, S., Marinov, Z., Li, K., Ye, Z., Krieg, S., Kleesiek, J., & Stiefelhagen, R. (2025). Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks. Proceedings of the AAAI Conference on Artificial Intelligence, 39(4), 3904–3912. https://ojs.aaai.org/index.php/AAAI/article/view/32408

Jia, X., Wang, Q., Wang, A., Wang, H. A., Gyenes, B., Gospodinov, E., Jiang, X., Li, G., Zhou, H., Liao, W., Huang, X., Beck, M., Reuss, M., Lioutikov, R., & Neumann, G. (2025). PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning. https://doi.org/10.48550/arXiv.2510.20406

Johnson, K. E., Tang, M. L., Tyszka, E., Jones, L., Nemcova, B., Wolffram, D., Ergas, R., Reich, N. G., Funk, S., Mellor, J., Bracher, J., & Abbott, S. (2025). Baseline nowcasting methods for handling delays in epidemiological data (S. 2025.08.14.25333653). https://doi.org/10.1101/2025.08.14.25333653

Krohmann, S., Rank, S., Schmidt-Kraepelin, M., Thiebes, S., & Sunyaev, A. (2025). Quest for quality: A review of design knowledge on gamified AI training data annotation systems. Behaviour & Information Technology, 0(0), 1–26. https://doi.org/10.1080/0144929X.2025.2568932

Kusch, J., Schotthöfer, S., & Walter, A. (2025). An Augmented Backward-Corrected Projector Splitting Integrator for Dynamical Low-Rank Training. https://doi.org/10.48550/arXiv.2502.03006

Lautenschlager, T., Friederich, N., Sitcheu, A. J. Y., Nau, K., Hayot, G., Dickmeis, T., & Mikut, R. (2025). Self-Supervised Learning Strategies for a Platform to Test the Toxicity of New Chemicals and Materials. https://doi.org/10.48550/arXiv.2510.07853

Liu, Y., Dufourq, E., Fransson, P., & Rocklöv, J. (2025). A comparison of deep neural network compression for citizen-driven tick and mosquito surveillance. Ecological Informatics, 92, 103437. https://doi.org/10.1016/j.ecoinf.2025.103437

Mayer, L., Kalinowski, P., Ebersbach, C., Knopp, M., Rädsch, T., Christodoulou, E., Reinke, A., Kolbinger, F. R., & Maier-Hein, L. (2025). 6 Fingers, 1 Kidney: Natural Adversarial Medical Images Reveal Critical Weaknesses of Vision-Language Models https://doi.org/10.48550/arXiv.2512.04238

Metzner, M., Schlechter, A., Zhevachevska, D., Schlegel, P., Jäkel, O., Martišíková, M., & Gehrke, T. (2025). 2.5D imaging: Obtaining depth information from 2D helium-beam radiographs*. Physics in Medicine & Biology, 70(20), 205017. https://doi.org/10.1088/1361-6560/ae02de

Neubert, M., Reiser, P., Gräter, F., & Friederich, P. (2025). Learning Potential Energy Surfaces of Hydrogen Atom Transfer Reactions in Peptides https://doi.org/10.48550/arXiv.2508.00578

Ortkamp, T., Sallem, H., Harrabi, S., Frank, M., Jäkel, O., Bauer, J., & Wahl, N. (2025). Let’s play POLO: Integrating the probability of lesion origin into proton treatment plan optimization for low-grade glioma patients. https://doi.org/10.48550/arXiv.2506.13539

Piochowiak, M., Kurpicz, F., & Dachsbacher, C. (2025). Random Access Segmentation Volume Compression for Interactive Volume Rendering. Computer Graphics Forum, 44(3), e70116. https://doi.org/10.1111/cgf.70116

Reiß, S., Marinov, Z., Jaus, A., Seibold, C., Sarfraz, M. S., Rodner, E., & Stiefelhagen, R. (2025). Is Visual in-Context Learning for Compositional Medical Tasks within Reach?. https://doi.org/10.48550/arXiv.2507.00868

Rokuss, M., Hamm, B., Kirchhoff, Y., & Maier-Hein, K. (2025). Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation (No.. https://doi.org/10.48550/arXiv.2507.13830

Rokuss, M., Langenberg, M., Kirchhoff, Y., Isensee, F., Hamm, B., Ulrich, C., Regnery, S., Bauer, L., Katsigiannopulos, E., Norajitra, T., & Maier-Hein, K. (2025). VoxTell: Free-Text Promptable Universal 3D Medical Image Segmentation https://doi.org/10.48550/arXiv.2511.11450

Roy, S., Kirchhoff, Y., Ulrich, C., Rokuss, M., Wald, T., Isensee, F., & Maier-Hein, K. (2025). MedNeXt-v2: Scaling 3D ConvNeXts for Large-Scale Supervised Representation Learning in Medical Image Segmentation. https://doi.org/10.48550/arXiv.2512.17774

Schlegel, P., Kirchgaessner, R., Ochoa Parra, P., Kelleter, L., Gertz, M., Mikut, R., Jäkel, O., & Martišíková, M. (2025). A data analysis framework for in vivo monitoring in carbon-ion radiotherapy (CIRT): Towards 3D reconstruction of interfractional anatomical changes. Physics in Medicine & Biology, 70(24), 245009. https://doi.org/10.1088/1361-6560/ae22bb

Schneider, D., Marinov, Z., Baur, R., Zhong, Z., Düger, R., & Stiefelhagen, R. (2025). OmniFall: A Unified Staged-to-Wild Benchmark for Human Fall Detection (No.. https://doi.org/10.48550/arXiv.2505.19889

Seidlitz, S., Hölzl, K., von Garrel, A., Sellner, J., Katzenschlager, S., Hölle, T., Fischer, D., von der Forst, M., Schmitt, F. C. F., Studier-Fischer, A., Weigand, M. A., Maier-Hein, L., & Dietrich, M. (2025). AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients. Science Advances, 11(29), eadw1968. https://doi.org/10.1126/sciadv.adw1968

Tran Ba, V., Hübner, M., Bin Qasim, A., Rees, M., Sellner, J., Seidlitz, S., Christodoulou, E., Özdemir, B., Studier-Fischer, A., Nickel, F., Ayala, L., & Maier-Hein, L. (2025). Semantic hyperspectral image synthesis for cross-modality knowledge transfer in surgical data science. International Journal of Computer Assisted Radiology and Surgery, 20(6), 1205–1213. https://doi.org/10.1007/s11548-025-03364-7

Treskova, M., Montalvo, T., Rocklöv, J., Hatfield, C., Bartumeus, F., Dasgupta, S., Encarnação, J., Lowe, R., Semenza, J. C., Stiles, P., Noya, J., Valsecchi, A., Bärnighausen, T., Palmer, J. R. B., & Bunker, A. (2025). Effects of mosquito-proofing storm drains on adult and larval mosquito abundance: Protocol of the IDAlErt storm drAin randomiSed controlled trial (IDEAS). MethodsX, 14, 103102. https://doi.org/10.1016/j.mex.2024.103102

Upadhyay, U., Herold, J., Götz, M., & Schug, A. (2025). NucleicBERT: Deciphering the language of nucleic acids by a large-language model (S. 2025.09.02.673754). bioRxiv. https://doi.org/10.1101/2025.09.02.673754

Upadhyay, U., Pucci, F., Herold, J., & Schug, A. (2025). NucleoSeeker-Precision filtering of RNA databases to curate high-quality datasets. NAR Genomics and Bioinformatics, 7(1), lqaf021. https://doi.org/10.1093/nargab/lqaf021

Vonficht, D., Jopp-Saile, L., Yousefian, S., Flore, V., Simó Vesperinas, I., Teuber, R., Avanesyan, B., Luo, Y., Röthemeier, C., Grünschläger, F., Fernandez-Vaquero, M., Fregona, V., Ordoñez-Rueda, D., Schmalbrock, L. K., Deininger, L., Yamachui Sitcheu, A. J., Gu, Z., Funk, M. C., Mikut, R., … Haas, S. (2025). Ultra-high-scale cytometry-based cellular interaction mapping. Nature Methods, 22(9), 1887–1899. https://doi.org/10.1038/s41592-025-02744-w

Walter, A., Bauer, C. J., Yawson, A. K., Hoegen-Saßmannshausen, P., Adeberg, S., Debus, J., Jäkel, O., Frank, M., & Giske, K. (2025). Accuracy of an articulated head-and-neck motion model using deep learning-based instance segmentation of skeletal bones in CT scans for image registration in radiotherapy. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 13(1), 2455752. https://doi.org/10.1080/21681163.2025.2455752

Wolffram, D., Bracher, J., Group, T. R. S., & Schienle, M. (2025). Integrating Nowcasts into an Ensemble of Data-Driven Forecasting Models for SARI Hospitalizations in Germany (S. 2025.02.21.25322655). https://doi.org/10.1101/2025.02.21.25322655

Zhou, C., Neubert, M., Koide, Y., Zhang, Y., Vuong, V.-Q., Schlöder, T., Dehnen, S., & Friederich, P. (2025). PAL – parallel active learning for machine-learned potentials. Digital Discovery, 4(7), 1901–1911. https://doi.org/10.1039/D5DD00073D

Zöllner, C., Reiß, S., Jaus, A., Sholi, A., Sodian, R., & Stiefelhagen, R. (2025). Semantic Segmentation for Preoperative Planning in Transcatheter Aortic Valve Replacement (No. arXiv:2507.16573). https://doi.org/10.48550/arXiv.2507.16573

Zwick, P., Friederich, N., Beichter, M., Hilbert, L., Mikut, R., & Bringmann, O. (2025). LeDiFlow: Learned Distribution-guided Flow Matching to Accelerate Image Generation. https://doi.org/10.48550/arXiv.2505.20723