Benjamin Hamm

According to our database, Benjamin Hamm authored at least 7 papers between 2024 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation.

Maximilian Rokuss, Benjamin Hamm, Yannick Kirchhoff, Klaus H. Maier-Hein

CoRR, July, 2025

Inclusive, Differentially Private Federated Learning for Clinical Data.

Santhosh Parampottupadam, Melih Cosgun, Sarthak Pati, Maximilian Zenk, Saikat Roy, Dimitrios Bounias, Benjamin Hamm, Sinem Sav, Ralf Floca, Klaus H. Maier-Hein

CoRR, May, 2025

nnInteractive: Redefining 3D Promptable Segmentation.

Fabian Isensee, Maximilian Rokuss, Lars Krämer, Stefan Dinkelacker, Ashis Ravindran, Florian Stritzke, Benjamin Hamm, Tassilo Wald, Moritz Langenberg, Constantin Ulrich, Jonathan Deissler, Ralf Floca, Klaus H. Maier-Hein

CoRR, March, 2025

Abstract: Client Security Alone Fails in Federated Learning - 2D and 3D Attack Insights.

Santhosh Parampottupadam, Ralf Floca, Dimitrios Bounias, Benjamin Hamm, Saikat Roy, Sinem Sav, Maximilian Zenk, Klaus H. Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

2024

Optimizing nnU-Net with OpenVINO for Fast CPU Inference in Abdominal Organ Segmentation.

Yannick Kirchhoff, Ashis Ravindran, Maximilian Rokuss, Benjamin Hamm, Constantin Ulrich, Klaus H. Maier-Hein, Fabian Isensee

Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Efficient Cross-Modality Abdominal Organ Segmentation Using nnU-Net and MIND Descriptors.

Yannick Kirchhoff, Maximilian Rokuss, Benjamin Hamm, Ashis Ravindran, Constantin Ulrich, Klaus H. Maier-Hein, Fabian Isensee

Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Efficient Pan-Cancer Lesion Segmentation from Partially Labeled Data with nnU-Net.

Yannick Kirchhoff, Maximilian Rokuss, Benjamin Hamm, Ashis Ravindran, Constantin Ulrich, Klaus H. Maier-Hein, Fabian Isensee

Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024