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61.
di Folco, M. ; Bercea, C.-I. ; Chan, E. & Schnabel, J.A.: Interpretable representation learning of cardiac MRI via attribute regularization. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 492-501 (Lect. Notes Comput. Sc. ; 15010)
62.
Eichhorn, H. et al.: Physics-informed deep learning for motion-corrected reconstruction of quantitative brain MRI. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 562-571 (Lect. Notes Comput. Sc. ; 15007)
63.
Erdur, A.C.* et al.: All Sizes Matter: Improving volumetric brain segmentation on small lesions. In: (Brain Tumor Segmentation, and Cross-Modality Domain Adaptation for Medical Image Segmentation). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 177-189 (Lect. Notes Comput. Sc. ; 14669 LNCS)
64.
Fischer, S.M. et al.: Progressive growing of patch size: Resource-efficient curriculum learning for dense prediction tasks. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). 2024. 510-520 (Lect. Notes Comput. Sc. ; 15009 LNCS)
65.
Galter, I. ; Schneltzer, E. ; Marr, C. ; Spielmann, N. & Hrabě de Angelis, M.: EchoVisuAL: Efficient Segmentation of Echocardiograms Using Deep Active Learning. In: (Medical Image Understanding and Analysis). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 366-381 (Lect. Notes Comput. Sc. ; 14860 LNCS)
66.
Gräf, L. ; Sens, D. ; Shilova, L. & Casale, F.P.: Disease risk predictions with differentiable mendelian randomization. In: (Research in Computational Molecular Biology). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 385-389 (Lect. Notes Comput. Sc. ; 14758 LNCS)
67.
Hartog, P. et al.: Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse. In: AI in Drug Discovery. Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 98-115 (Lect. Notes Comput. Sc. ; 14894 LNCS)
68.
Koch, V. et al.: DinoBloom: A foundation model for generalizable cell embeddings in hematology. In: (Computer Vision and Pattern Recognition). 2024. 520-530 (Lect. Notes Comput. Sc. ; 15012 LNCS)
69.
Kogl, F. et al.: General vision encoder features as guidance in medical image registration. In: (Biomedical Image Registration). 2024. 265-279 (Lect. Notes Comput. Sc. ; 15249 LNCS)
70.
Linguraru, M.G.* et al.: Preface. Lect. Notes Comput. Sc. 15002 LNCS, vii-ix (2024)
71.
Linguraru, M.G.* et al.: Preface. Lect. Notes Comput. Sc. 15012 LNCS, vii-ix (2024)
72.
Linguraru, M.G.* et al.: Preface. Lect. Notes Comput. Sc. 15007 LNCS, v-ix (2024)
73.
Machado, I.P.* et al.: A self-supervised image registration approach for measuring local response patterns in metastatic ovarian cancer. In: (Biomedical Image Registration). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 295-307 (Lect. Notes Comput. Sc. ; 15249 LNCS)
74.
Madni, H.A.* ; Umer, R.M. & Foresti, G.L.*: Federated learning for data and model heterogeneity in medical imaging. In: (ICIAP 2023: Image Analysis and Processing - ICIAP 2023 Workshops). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 167-178 (Lect. Notes Comput. Sc. ; 14366)
75.
Mueller, T.T.* et al.: Extended graph assessment metrics for regression and weighted graphs. In:. Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 14-26 (Lect. Notes Comput. Sc. ; 14373 LNCS)
76.
Osuala, R. et al.: Towards learning contrast kinetics with multi-condition latent diffusion models. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 713-723 (Lect. Notes Comput. Sc. ; 15005 LNCS)
77.
Reithmeir, A. ; Felsner, L. ; Braren, R.* ; Schnabel, J.A. & Zimmer, V.A.: Data-driven tissue- and subject-specific elastic regularization for medical image registration. In: (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024). 2024. 575-585 (Lect. Notes Comput. Sc. ; 15002 LNCS)
78.
Roider, J.* ; Zanca, D.* & Eskofier, B.M.: Efficient training of recurrent neural networks for remaining time prediction in predictive process monitoring. In: (Business Process Management). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 238-255 (Lect. Notes Comput. Sc. ; 14940 LNCS)
79.
Sadafi, A. et al.: A continual learning approach for cross-domain white blood cell classification. In: (Domain Adaptation and Representation Transfer). Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 136-146 (Lect. Notes Comput. Sc. ; 14293 LNCS)
80.
Spieker, V. et al.: ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. In: Deep Generative Models. Gewerbestrasse 11, Cham, Ch-6330, Switzerland: Springer International Publishing Ag, 2024. 183-192 (Lect. Notes Comput. Sc. ; 14533 LNCS)
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