Hamza Kalisch

According to our database, Hamza Kalisch authored at least 7 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2026

The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT - Multitracer Multicenter Generalization.

Jakob Dexl, Katharina Jeblick, Andreas Mittermeier, Balthasar Schachtner, Anna Theresa Stüber, Johanna Topalis, Maximilian Rokuss, Fabian Isensee, Klaus H. Maier-Hein, Hamza Kalisch, Jens Kleesiek, Constantin Marc Seibold, Hussain Alasmawi, Lap Yan Lennon Chan, Yixuan Yuan, Alexander Jaus, Rainer Stiefelhagen, Pauline Ornela Megne Choudja, Konstantin Nikolaou, Christian la Fougère, Sergios Gatidis, Matthias Fabritius, Maurice Heimer, Gizem Abaci, Lalith Kumar Shiyam Sundar, Rudolf A. Werner, Jens Ricke, Clemens C. Cyran, Thomas Küstner, Michael Ingrisch

CoRR, May, 2026

Region-Normalized DPO for Medical Image Segmentation under Noisy Judges.

Hamza Kalisch, Constantin Seibold, Jens Kleesiek, Ken Herrmann, Frederic Jonske

CoRR, January, 2026

2025

Automatic Fine-grained Segmentation-assisted Report Generation.

Frederic Jonske, Constantin Seibold, Osman Alperen Koras, Fin Hendrik Bahnsen, Marie Bauer, Amin Dada, Hamza Kalisch, Anton Schily, Jens Kleesiek

CoRR, July, 2025

Foreign object segmentation in chest x-rays through anatomy-guided shape insertion.

Constantin Seibold, Hamza Kalisch, Lukas Heine, Simon Reiß, Jens Kleesiek

CoRR, January, 2025

CT-GRAPH: Hierarchical Graph Attention Network for Anatomy-Guided CT Report Generation.

Hamza Kalisch, Fabian Hörst, Jens Kleesiek, Ken Herrmann, Constantin Seibold

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

2024

Autopet III challenge: Incorporating anatomical knowledge into nnUNet for lesion segmentation in PET/CT.

Hamza Kalisch, Fabian Hörst, Ken Herrmann, Jens Kleesiek, Constantin Seibold

CoRR, 2024

2023

Exploring the Limits of Deep Image Clustering using Pretrained Models.

Nikolas Adaloglou, Felix Michels, Hamza Kalisch, Markus Kollmann

Proceedings of the 34th British Machine Vision Conference 2023, 2023