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1.
Alaya, M.B.* ; Lang, D.M. ; Wiestler, B.* ; Schnabel, J.A. & Bercea, C.-I.: MedEdit: Counterfactual diffusion-based image editing on brain MRI. In: (Simulation and Synthesis in Medical Imaging). 2025. 167-176 (Lect. Notes Comput. Sc. ; 15187 LNCS)
2.
Chobola, T. ; Liu, Y.* ; Zhang, H. ; Schnabel, J.A. & Peng, T.: Fast context-based low-light image enhancement via neural implicit representations. In: (Computer Vision – ECCV 2024). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 413-430 (Lect. Notes Comput. Sc. ; 15144)
3.
Daum, D. et al.: On differentially private 3D medical image synthesis with controllable latent diffusion models. In: (Deep Generative Models). 2025. 139-149 (Lect. Notes Comput. Sc. ; 15224 LNCS)
4.
Daza, L. & Schnabel, J.A.: DiENTeS: Dynamic ENTity segmentation with local-global transformers. In: (Supervised and Semi-supervised Multi-structure Segmentation and Landmark Detection in Dental Data). 2025. 21-29 (Lect. Notes Comput. Sc. ; 15571 LNCS)
5.
Duelmer, F. et al.: PHOCUS: Physics-based deconvolution for ultrasound resolution enhancement. In: (Simplifying Medical Ultrasound). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 35-44 (Lect. Notes Comput. Sc. ; 15186 LNCS)
6.
Durrer, A.* et al.: Denoising diffusion models for 3D healthy brain tissue inpainting. In: (Deep Generative Models). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 87-97 (Lect. Notes Comput. Sc. ; 15224 LNCS)
7.
Farjallah, E.* et al.: Affordable deep learning for diagnosing inherited and common retinal diseases via color fundus photography. In: (Ophthalmic Medical Image Analysis). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 83-93 (Lect. Notes Comput. Sc. ; 15188 LNCS)
8.
Garrucho, L.* et al.: Fat-suppressed breast MRI synthesis for domain adaptation in tumour segmentation. In: (Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care). 2025. 202-211 (Lect. Notes Comput. Sc. ; 15451 LNCS)
9.
Hummel, T. ; Karthik, S. ; Georgescu, M.-I. & Akata, Z.: EgoCVR: An egocentric benchmark for fine-grained composed video retrieval. In: (18th European Conference on Computer Vision, ECCV 2024, 29 September - 4 October 2024, Milan). 2025. 1-17 (Lect. Notes Comput. Sc. ; 15095 LNCS)
10.
Kaess, P.* et al.: Fair and private CT contrast agent detection. In: (Ethics and Fairness in Medical Imaging). 2025. 34-45 (Lect. Notes Comput. Sc. ; 15198 LNCS)
11.
Kiechle, J. et al.: Graph Neural Networks: A Suitable Alternative to MLPs in Latent 3D Medical Image Classification? In: (Graphs in Biomedical Image Analysis). 2025. 12–22 (Lect. Notes Comput. Sc.)
12.
Kim, J.M. ; Bader, J. ; Alaniz, S. ; Schmid, C.* & Akata, Z.: DataDream: Few-shot guided dataset generation. In: (Computer Vision – ECCV 2024). 2025. 252-268 (Lect. Notes Comput. Sc. ; 15129 LNCS)
13.
Li, J.* et al.: Language models meet anomaly detection for better interpretability and generalizability. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). 2025. 113-123 (Lect. Notes Comput. Sc. ; 15401 LNCS)
14.
Litinetskaya, A. et al.: Integration and querying of multimodal single-cell data with PoE-VAE. In: (29th RECOMB 2025). 2025. 345-348 (Lect. Notes Comput. Sc. ; 15647 LNBI)
15.
Merzhevich, T.* et al.: Machine Learning Predictions of Overall and Progression-Free Survival in Advanced Breast Cancer. In: (Artificial Intelligence in Medicine). 2025. 267-271 (Lect. Notes Comput. Sc. ; 15735 LNAI)
16.
Mykula, H.* et al.: Diffusion models for unsupervised anomaly detection in fetal brain ultrasound. In: (Simplifying Medical Ultrasound). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 220-230 (Lect. Notes Comput. Sc. ; 15186 LNCS)
17.
Nappi, A. ; Cai, N. & Casale, F.P.: Bayesian aggregation of multiple annotations enhances rare variant association testing. In: (Research in Computational Molecular Biology). 2025. 428-431 (Lect. Notes Comput. Sc. ; 15647 LNBI)
18.
Osuala, R. et al.: Enhancing the utility of privacy-preserving cancer classification using synthetic data. In: (Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care). 2025. 54-64 (Lect. Notes Comput. Sc. ; 15451 LNCS)
19.
Rasheed, H. et al.: Learning to match 2D keypoints across preoperative MR and intraoperative ultrasound. In: (Simplifying Medical Ultrasound). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 78-87 (Lect. Notes Comput. Sc. ; 15186 LNCS)
20.
Riess, A. et al.: Complex-valued federated learning with differential privacy and MRI applications. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2025. 191-203 (Lect. Notes Comput. Sc. ; 15274 LNCS)
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