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ORCIDJohannes Kiechle
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2020 – today
- 2024
[c3]Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang, Maxime Di Folco, Sarah C. Foreman, Verena K. N. Rösner, Ann-Kathrin Lohse, Carolin Mogler, Carolin Knebel, Marcus R. Makowski, Klaus Woertler, Stephanie E. Combs, Alexandra S. Gersing, Jan C. Peeken, Julia A. Schnabel:
Unifying Local and Global Shape Descriptors to Grade Soft-Tissue Sarcomas Using Graph Convolutional Networks. ISBI 2024: 1-5- [c2]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. MICCAI (9) 2024: 510-520 - [i4]Jakaria Rabbi, Johannes Kiechle, Christian Beaulieu, Nilanjan Ray, Dana Cobzas:
Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Graph Variational Autoencoder with Contrastive Learning. CoRR abs/2404.00785 (2024) - [i3]Stefan M. Fischer, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge. CoRR abs/2406.14365 (2024) - [i2]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. CoRR abs/2407.07853 (2024) - [i1]Johannes Kiechle, Daniel M. Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel:
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification? CoRR abs/2407.17219 (2024) - 2023
- [c1]Johannes Kiechle, Dylan Miller, Jordan Slessor, Matthew Pietrosanu, Linglong Kong, Christian Beaulieu, Dana Cobzas:
Explaining Anatomical Shape Variability: Supervised Disentangling with A Variational Graph Autoencoder. ISBI 2023: 1-5
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