5 citations · 6 across the 4 of their papers we have counts for
4 papers
Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis
Qiwen Xu, David Rügamer, Holger Wenz +4
Digital subtraction angiography (DSA) plays a central role in the diagnosis and treatment of cerebrovascular disease, yet its invasive nature and high acquisition cost severely lim…
Deep learning and abstractive summarisation for radiological reports: an empirical study for adapting the PEGASUS models' family with scarce data
Claudio Benzoni, Martina Langhals, Martin Boeker +2
Regardless of the rapid development of artificial intelligence, abstractive summarisation is still challenging for sensitive and data-restrictive domains like medicine. With the in…
Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI
Nazanin Maleki, Raisa Amiruddin, Ahmed W. Moawad +240
Despite continuous advancements in cancer treatment, brain metastatic disease remains a significant complication of primary cancer and is associated with an unfavorable prognosis.…
Simple statistical methods for unsupervised brain anomaly detection on MRI are competitive to deep learning methods
Victor Saase, Holger Wenz, Thomas Ganslandt +2
Statistical analysis of magnetic resonance imaging (MRI) can help radiologists to detect pathologies that are otherwise likely to be missed. Deep learning (DL) has shown promise in…