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81.
An, U.* ; Cai, N. ; Dahl, A.* & Sankararaman, S.*: AutoComplete: Deep learning-based phenotype imputation for large-scale biomedical data. Lect. Notes Comput. Sc. 13278 LNBI, 385-386 (2022)
82.
Heinrich, M.* et al.: Preface. Lect. Notes Comput. Sc. 13386 LNCS, v-vi (2022)
83.
Horoi, S.* et al.: Exploring the geometry and topology of neural network loss landscapes. Lect. Notes Comput. Sc. 13205 LNCS, 171-184 (2022)
84.
Jian, B.* et al.: Weakly-supervised biomechanically-constrained CT/MRI registration of the spine. Lect. Notes Comput. Sc. 13436 LNCS, 227-236 (2022)
85.
Kazeminia, S. et al.: Anomaly-aware multiple instance learning for rare anemia disorder classification. Lect. Notes Comput. Sc. 13438 LNCS, 341-350 (2022)
86.
Koch, V. et al.: Noise transfer for unsupervised domain adaptation of retinal OCT images. Lect. Notes Comput. Sc. 13432 LNCS, 699-708 (2022)
87.
Lang, D.M. ; Peeken, J.C. ; Combs, S.E. ; Wilkens, J.J.* & Bartzsch, S.: Deep learning based GTV delineation and progression free survival risk score prediction for head and neck cancer patients. In: (HECKTOR 2021: Head and Neck Tumor Segmentation and Outcome Prediction, 27 September 2021, Virtual, Online). 2022. 150-159 (Lect. Notes Comput. Sc. ; 13209 LNCS)
88.
Lang, D.M. ; Peeken, J.C. ; Combs, S.E. ; Wilkens, J.J.* & Bartzsch, S.: A video data based transfer learning approach for classification of MGMT status in brain tumor MR images. Lect. Notes Comput. Sc. 12962 LNCS, 306-314 (2022)
89.
Liu, Y.* et al.: DeStripe: A Self2Self spatio-spectral graph neural network with unfolded hessian for stripe artifact removal in light-sheet microscopy. Lect. Notes Comput. Sc. 13434 LNCS, 99-108 (2022)
90.
Machado, I.* et al.: Quality-aware cine cardiac MRI reconstruction and analysis from undersampled K-space data. Lect. Notes Comput. Sc. 13131 LNCS, 12-20 (2022)
91.
Mächler, L.* et al.: FedCostWAvg: A new averaging for better federated learning. Lect. Notes Comput. Sc. 12963 LNCS, 383-391 (2022)
92.
Reisenbüchler, D. ; Wagner, S. ; Boxberg, M.* & Peng, T.: Local attention graph-based transformer for multi-target genetic alteration prediction. Lect. Notes Comput. Sc. 13432 LNCS, 377-386 (2022)
93.
Salehi, R. et al.: Unsupervised cross-domain feature extraction for single blood cell image classification. Lect. Notes Comput. Sc. 13433 LNCS, 739-748 (2022)
94.
Shetab Boushehri, S. ; Qasim, A.B. ; Waibel, D.J.E. ; Schmich, F.* & Marr, C.: Systematic comparison of incomplete-supervision approaches for biomedical image classification. Lect. Notes Comput. Sc. 13529 LNCS, 355-365 (2022)
95.
Starke, S.* ; Thalmeier, D. ; Steinbach, P.* & Piraud, M.: A hybrid radiomics approach to modeling progression-free survival in head and neck cancers. In: (HECKTOR 2021: Head and Neck Tumor Segmentation and Outcome Prediction, Virtual, Online). 2022. 266-277 (Lect. Notes Comput. Sc. ; 13209 LNCS)
96.
Tomczak, A.* ; Gupta, A.* ; Ilic, S.* ; Navab, N.* & Albarqouni, S.: What can we learn about a generated image corrupting its latent representation? Lect. Notes Comput. Sc. 13436 LNCS, 505-515 (2022)
97.
Tran, M. ; Wagner, S. ; Boxberg, M.* & Peng, T.: S5CL: Unifying fully-supervised, self-supervised, and semi-supervised learning through hierarchical contrastive learning. Lect. Notes Comput. Sc. 13432 LNCS, 99-108 (2022)
98.
Ugurlu, D.* et al.: The impact of domain shift on left and right ventricle segmentation in short axis cardiac MR images. Lect. Notes Comput. Sc. 13131 LNCS, 57-65 (2022)
99.
Waibel, D.J.E. ; Atwell, S. ; Meier, M. ; Marr, C. & Rieck, B.: Capturing shape information with multi-scale topological loss terms for 3D reconstruction. Lect. Notes Comput. Sc. 13434 LNCS, 150-159 (2022)
100.
Albarqouni, S. ; Khanal, B.* ; Rekik, I.* ; Rieke, N.* & Sheet, D.*: Preface FAIR 2021. Lect. Notes Comput. Sc. 12968 LNCS, vii-viii (2021)
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