Publications 2024

Journal articles

• Walter, A., Hoegen-Sasmannshausen, P., Stanic, G., Rodrigues, J. P., Adeberg, S., Jäkel, O., Frank, M. & Giske, K. (2024). Segmentation of 71 Anatomical Structures Necessary for the Evaluation of Guideline-Conforming Clinical Target Volumes in Head and Neck Cancers. Cancers, 16(2). DOI: 10.3390/cancers16020415

•  Yawson, A. K., Walter, A., Wolf, N., Klüter, S., Hoegen, P., Adeberg, S., ... & Giske, K. (2024). Essential parameters needed for a U-Net-based segmentation of individual bones on planning CT images in the head and neck region using limited datasets for radiotherapy application. Physics in Medicine & Biology, 69(3), 035008. DOI: 10.1088/1361-6560/ad1b6e

• Toussaint, P. A., Leiser, F., Thiebes, S., Schlesner, M., Brors, B., Sunyaev, A. (2024). Explainable artificial intelligence for omics data: a systematic mapping study. Briefings in Bioinformatics, 25(1), 1–16. DOI: 10.1093/bib/bbad453

• Marinov, Z., Jäger, P. F., Egger, J., Kleesiek, J., & Stiefelhagen, R. (2024). Deep interactive segmentation of medical images: A systematic review and taxonomy. IEEE Transactions on Pattern Analysis and Machine Intelligence. DOI: 10.1109/TPAMI.2024.3364045

• Gatidis, S., Früh, M., Fabritius, M. P., Gu, S., Nikolaou, K., Fougère, C. L., Ye, J., He, J., Peng, Y., Bi, L., Ma, J., Wang, B., Zhang, J., Huang, Y., Heiliger, L., Marinov, Z., Stiefelhagen, R., Egger, J., Kleesiek, J., Sibille, L., Xiang, L., Bendazzoli, S., Astaraki, M., Ingrisch, M., Cyran, C. C. & Küstner, T. (2024). Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging. Nature Machine Intelligence, 1-10. DOI: 10.1038/s44260-024-00011-1

• Studier-Fischer, A., Özdemir, B., Rees, M., Ayala, L., Seidlitz, S., Sellner, J., Kowalewski, K.-F., Haney, C. M., Odenthal, J., Knödler, S., Dietrich, M., Gruneberg, D., Brenner, T., Schmidt, K., Schmitt, F. C. F., Weigand, M. A., Salg, G. A., Dupree, A., Nienhüser, H., ... & Nickel, F. (2024). Crystalloid volume versus catecholamines for management of hemorrhagic shock during esophagectomy: assessment of microcirculatory tissue oxygenation of the gastric conduit in a porcine model using hyperspectral imaging – an experimental study. International Journal of Surgery, 110(10), 6558–6572. DOI: 10.1097/js9.0000000000001849

• Studier-Fischer, A., Bressan, M., Qasim, A. bin, Özdemir, B., Sellner, J., Seidlitz, S., Haney, C. M., Egen, L., Michel, M., Dietrich, M., Salg, G. A., Billmann, F., Nienhüser, H., Hackert, T., Müller, B. P., Maier-Hein, L., Nickel, F., & Kowalewski, K. F. (2024). Spectral characterization of intraoperative renal perfusion using hyperspectral imaging and artificial intelligence. Scientific Reports, 14(1). DOI: 10.1038/s41598-024-68280-3

• Ayala, L., Mindroc-Filimon, D., Rees, M., Hübner, M., Sellner, J., Seidlitz, S., Tizabi, M., Wirkert, S., Seitel, A., & Maier-Hein, L. (2024). The SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA) for video-rate functional imaging of the skin. Scientific Data, 11(1). DOI: 10.1038/s41597-024-03307-y

• Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M. D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., Reyes, M., Riegler, M. A., Wiesenfarth, M., Kavur, A. E., Sudre, C. H., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Rädsch, T., ... & Jäger, P. F. (2024). Metrics reloaded: recommendations for image analysis validation. Nature Methods, 21(2), 195–212. DOI: 10.1038/s41592-023-02151-z

• • Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Buettner, F., Cardoso, M. J., Cheplygina, V., Chen, J., Christodoulou, E., Cimini, B. A., ..., Godau, P., ... & Maier-Hein, L. (2024). Understanding metric-related pitfalls in image analysis validation. Nature Methods, 21(2), 182–194. DOI: 10.1038/s41592-023-02150-0

• Zaunseder, E., Mütze, U., Okun, J. G., Hoffmann, G. F., Kölker, S., Heuveline, V., & Thiele, I. (2024). Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases. Cell Metabolism, 36(8), 1882–1897.e7. DOI: 10.1016/j.cmet.2024.05.006

• Schröter, J., Deininger, L., Lupse, B., Richter, P., Syrbe, S., Mikut, R., & Jung-Klawitter, S. (2024). A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids. Scientific Data, 11(1). DOI: 10.1038/s41597-024-03330-z

• Piochowiak, M., Dachsbacher, C. (2024). Fast Compressed Segmentation Volumes for Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics, 30(1), 12-22. DOI: 10.1109/TVCG.2023.3326573

• Werner, M., Piochowiak, M., & Dachsbacher, C. (2024). SVDAG Compression for Segmentation Volume Path Tracing. In Vision, Modeling, and Visualization. The Eurographics Association. DOI: 10.2312/vmv.20241196

• Dolp, R., Hanika, J., Dachsbacher, C. (2024). A Fast GPU Schedule For À-Trous Wavelet-Based Denoisers. Proceedings of the ACM on Computer Graphics and Interactive Techniques.

• Schlegel, P., Kelleter, L., Parra, P. O., Bartelme, E., Kirchgässner, R., Jaekel, O., Debus, J., & Martišíková, M. (2024). Carbon-ion radiotherapy monitoring with secondary ions: New data analysis strategies for detecting inter-fractional changes. International Journal of Particle Therapy, 12(Supplement). DOI: 10.1016/j.ijpt.2024.100315

• Zaunseder, E., Teinert, J., Boy, N., Garbade, S. F., Haupt, S., Feyh, P., Hoffmann, G. F., Kölker, S., Mütze, U., Heuveline, V. (2024). Digital-tier strategy improves newborn screening for glutaric aciduria type 1. International Journal of Neonatal Screening.

Conference Papers and Proceedings

• Staniek, M. & Fracarolli, M. & Hagmann, M. & Riezler, S. (2024). Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series Forecasting. Proceedings of Machine Learning Research (MLHC), 252.

• Disch, N., et al. (2024). Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series. In Springer Lecture Notes in Computer Science, LDTM Workshop, MICCAI 2024, Marrakesh.

• Toussaint, P. A., Warsinsky, S. L., Schmidt-Kraepelin, M., Thiebes, S., Sunyaev, A. (2024). Designing Gamification Concepts for Expert Explainable Artificial Intelligence Evaluation Tasks: A Problem Space Exploration. Proceedings of the 57th Hawaii International Conference on System Sciences, Honolulu, HI, 3rd - 6th January 2024.

• Schmidt-Kraepelin, M., Ben Ayed, M., Warsinsky, S. L., Hu, S., Thiebes, S., Sunyaev, A. (2024). Leaderboards in Gamified Information Systems for Health Behavior Change: The Role of Positioning, Psychological Needs, and Gamification User Types. Proceedings of the 57th Hawaii International Conference on System Sciences, Honolulu, HI, 3rd - 6th January 2024.

• Thiebes, S., Schmidt-Kraepelin, M., Toussaint, P.A., Lyytinen, K., & Sunyaev, A. (2024). Privacy-Utility Trade-Offs in Genetic Data Sharing and the Moderating Role of Social Distance: An Interdependent Privacy Calculus. ICIS 2024 Proceedings.
• https://aisel.aisnet.org/icis2024/security/security/8

• Kirchhoff, Y., Rokuss, M. R., Roy, S., Kovacs, B., Ulrich, C., Wald, T., Vollmuth, P., Kleesiek, J., Isensee, F., Maier-Hein, K. (2024). Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures. In Computer Vision – ECCV 2024, Lecture Notes in Computer Science, vol 15135. Springer, Cham. DOI: 10.1007/978-3-031-72089-5_12

• Rokuss, M., Kirchhoff, Y., Roy, S., Kovacs, B., Ulrich, C., Wald, T., Zenk, M., Denner, S., Isensee, F., Vollmuth, P., Kleesiek, J., Maier-Hein, K. (2024). Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting. In Springer Lecture Notes in Computer Science, LDTM Workshop, MICCAI 2024, Marrakesh.

• Stock, R., Denner, S., Kirchhoff, Y., Ulrich, C., Rokuss, M. R., Roy, S., Disch, N., Maier-Hein, K. (2024). From Generalist to Specialist: Incorporating Domain-Knowledge into Flamingo for Chest X-Ray Report Generation. MIDL 2024 Shortpaper.

• Mora, A. M., Baumgartner, M., Brugnara, G., Zenk, M., Kirchhoff, Y., Rastogi, A., Radbruch, A., Bendszus, M., Sanchez, C. I., Vollmuth, P., Maier-Hein, K. (2024). Curriculum-learning for Vessel Occlusion Detection in Multi-site Brain CT Angiographies. MIDL 2024 Shortpaper.

• Khan-Blouki, V., Seiz, F., Walter, N., Jaus, A., Marinov, Z., Luijten, G., Egger, J., Seibold, C., Kleesiek, J., & Stiefelhagen, R. (2024). FootCapture: Towards an AR-based System for 3D Foot Object Acquisition through Photogrammetry. In Medical Imaging with Deep Learning (MIDL) Short paper track.

• Marinov, Z., Jaus, A., Kleesiek, J., & Stiefelhagen, R. (2024). Filters, Thresholds, and Geodesic Distances for Scribble-based Interactive Segmentation of Medical Images. In CVPR 2024: Segment Anything In Medical Images On Laptop.

• Marinov, Z., Kleesiek, J., & Stiefelhagen, R. (2024). Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods. In International Conference on Medical Image Computing and Computer-Assisted Intervention, Workshop on Advancing Data Solutions in Medical Imaging AI (ADSMI). Cham: Springer Nature Switzerland.

• Hadlich, M., Marinov, Z., Kim, M., Nasca, E., Kleesiek, J., & Stiefelhagen, R. (2024, May). Sliding window fastedit: A framework for lesion annotation in whole-body PET images. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.

• • Baumann, A., Ayala, L., Studier-Fischer, A., Sellner, J., Özdemir, B., Kowalewski, K.-F., Ilic, S., Seidlitz, S., & Maier-Hein, L. (2024). Deep Intra-operative Illumination Calibration of Hyperspectral Cameras. In Lecture Notes in Computer Science (pp. 120–131). Springer Nature Switzerland. DOI: 10.1007/978-3-031-72089-5_12

• Qasim, A. B., Motta, A., Studier-Fischer, A., Sellner, J., Ayala, L., Hübner, M., Bressan, M., Özdemir, B., Kowalewski, K. F., Nickel, F., Seidlitz, S., & Maier-Hein, L. (2024). Test-time augmentation with synthetic data addresses distribution shifts in spectral imaging. International Journal of Computer Assisted Radiology and Surgery, 19(6), 1021–1031. DOI: 10.1007/s11548-024-03085-3

• Ortkamp, T., Salomé, P., Jäkel, O., Frank, M. & Wahl, N. (2024). pyanno4rt: a Toolkit for Machine Learning (N)TCP Model-Based Inverse Radiotherapy Treatment Plan Optimization. In Proceedings of the XX-th international conference on the use of computers in radiation therapy (ICCR) (pp. 841-844). HAL (hal-04720234).

• Christodoulou, E., Reinke, A., Houhou, R., Kalinowski, P., Erkan, S., Sudre, C. H., Burgos, N., Boutaj, S., Loizillon, S., Solal, M., Rieke, N., Cheplygina, V., Antonelli, M., Mayer, L. D., Tizabi, M. D., Cardoso, M. J., Simpson, A., Jäger, P. F., Kopp-Schneider, A., ... & Maier-Hein, L. (2024). Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI? In Lecture Notes in Computer Science (pp. 124–132). Springer Nature Switzerland. DOI: 10.1007/978-3-031-72117-5_12

• Schneider, D., Reiß, S., Kugler, M., Jaus, A., Peng, K., Sutschet, S., ... & Stiefelhagen, R. (2024, October). Muscles in Time: Learning to Understand Human Motion In-Depth by Simulating Muscle Activations. In The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track.

• Jaus, A., Seibold, C., Reiß, S., Heine, L., Schily, A., Kim, M., ... & Kleesiek, J. (2024, October). Anatomy-guided Pathology Segmentation. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 3-13). Cham: Springer Nature Switzerland.

• Jaus, A., Seibold, C., Hermann, K., Shahamiri, N., Walter, A., Giske, K., ... & Stiefelhagen, R. (2024, October). Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset. In 2024 IEEE International Conference on Image Processing (ICIP) (pp. 41-47). IEEE.

• Friederich, N., Yamachui Sitcheu, A. J., Nassal, A., Pesch, M., Yildiz, E., Beichter, M., Scholtes, L., Akbaba, B., Lautenschlager, T., Neumann, O., Kohlheyer, D., Scharr, H., Seiffarth, J., Nöh, K., & Mikut, R. (2024). EAP4EMSIG - Experiment Automation Pipeline for Event-Driven Microscopy to Smart Microfluidic Single-Cells Analysis. KIT Scientific Publishing. DOI: 10.5445/IR/1000176752

• Gyenes, B., Franke, N., Becker, P., & Neumann, G. (2024). PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds. 8th Annual Conference on Robot Learning.
• https://openreview.net/forum?id=3jNEz3kUSl

Data Set and Software Publications

• Zhou, C., Neubert, M., Koide, Y., Zhang, Y., Vuong, V.-Q., Schlöder, T., Dehnen, S., Friederich, P. (2024). PAL -- Parallel active learning for machine-learned potentials. DOI: 10.48550/arXiv.2412.00401

• Schröter, J., Deininger, L., Lupse, B., Richter, P., Syrbe, S., Mikut, R., Jung-Klawitter, S. (2024). A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids. Scientific Data. DOI: 10.1038/s41597-024-03330-z