collaborators

14 papers

cs.CV2026

Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction

Johannes Kiechle, Richard Osuala, Daniel M. Lang +5

In patients with breast cancer, pathological complete response (pCR) has been established as a clinically meaningful surrogate marker for long-term outcomes. While commonly treated…

cs.CL2026

Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled Trial

Lisa C. Adams, Linus Marx, Erik Thiele Orberg +8

Question: Does atomic fact-checking, which decomposes AI treatment recommendations into individually verifiable claims linked to source guideline documents, increase clinician trus…

cs.CV2026

Deep-Learning Atlas Registration for Melanoma Brain Metastases: Preserving Pathology While Enabling Cohort-Level Analyses

Nanna E. Wielenberg, Ilinca Popp, Oliver Blanck +6

Melanoma brain metastases (MBM) are common and spatially heterogeneous lesions, complicating cohort-level analyses due to anatomical variability and differing MRI protocols. We pro…

cs.CV2026

LocBAM: Advancing 3D Patch-Based Image Segmentation by Integrating Location Contex

Donnate Hooft, Stefan M. Fischer, Cosmin Bercea +2

Patch-based methods are widely used in 3D medical image segmentation to address memory constraints in processing high-resolution volumetric data. However, these approaches often ne…

cs.CL2025

Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs

Juraj Vladika, Annika Domres, Mai Nguyen +10

Large language models (LLMs) exhibit extensive medical knowledge but are prone to hallucinations and inaccurate citations, which pose a challenge to their clinical adoption and reg…

eess.IV2025

TomoGraphView: 3D Medical Image Classification with Omnidirectional Slice Representations and Graph Neural Networks

Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang +5

The sharp rise in medical tomography examinations has created a demand for automated systems that can reliably extract informative features for downstream tasks such as tumor chara…