papers

Publications (6)

cs.CV2026

Region-Normalized DPO for Medical Image Segmentation under Noisy Judges

Hamza Kalisch, Constantin Seibold, Jens Kleesiek +2

While dense pixel-wise annotations remain the gold standard for medical image segmentation, they are costly to obtain and limit scalability. In contrast, many deployed systems alre…

cs.CV2024

Anatomy-guided Pathology Segmentation

Alexander Jaus, Constantin Seibold, Simon Reiß +7

Pathological structures in medical images are typically deviations from the expected anatomy of a patient. While clinicians consider this interplay between anatomy and pathology, r…

eess.IV2023

Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling

Constantin Seibold, Alexander Jaus, Matthias A. Fink +5

Purpose: Interpreting chest radiographs (CXR) remains challenging due to the ambiguity of overlapping structures such as the lungs, heart, and bones. To address this issue, we prop…

cs.CV2025

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

Hamza Kalisch, Fabian Hörst, Jens Kleesiek +2

As medical imaging is central to diagnostic processes, automating the generation of radiology reports has become increasingly relevant to assist radiologists with their heavy workl…

cs.CV2024

Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient Constraints

Jonas Nasimzada, Jens Kleesiek, Ken Herrmann +2

Recognizing pain in video is crucial for improving patient-computer interaction systems, yet traditional data collection in this domain raises significant ethical and logistical ch…

eess.IV2024

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

Hamza Kalisch, Fabian Hörst, Ken Herrmann +2

Lesion segmentation in PET/CT imaging is essential for precise tumor characterization, which supports personalized treatment planning and enhances diagnostic precision in oncology.…