43 citations
- Technical University of MunichDE9 papers
- TUM KlinikumDE9 papers
- Heidelberg UniversityDE6 papers
- University Hospital HeidelbergDE6 papers
- Charité - Universitätsmedizin BerlinDE5 papers
- RWTH Aachen UniversityDE5 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE4 papers
- Radboud University Medical CenterNL4 papers
- Radboud University NijmegenNL4 papers
- Else Kröner Fresenius Center for Digital HealthDE3 papers
- German Centre for Cardiovascular ResearchDE3 papers
- Harvard UniversityUS3 papers
6 papers · 1 filter
Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors
Jacqueline Lammert, Nicole Pfarr, Leonid Kuligin +16
Rare gynecological tumors (RGTs) present major clinical challenges due to their low incidence and heterogeneity. The lack of clear guidelines leads to suboptimal management and poo…
RadioRAG: Online Retrieval-augmented Generation for Radiology Question Answering
Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno Bressem +7
Large language models (LLMs) often generate outdated or inaccurate information based on static training datasets. Retrieval-augmented generation (RAG) mitigates this by integrating…
Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection
Felix J. Dorfner, Janis L. Vahldiek, Leonhard Donle +15
Purpose: To examine whether incorporating anatomical awareness into a deep learning model can improve generalizability and enable prediction of disease progression. Methods: This r…
MRSegmentator: Multi-Modality Segmentation of 40 Classes in MRI and CT
Hartmut Häntze, Lina Xu, Christian J. Mertens +29
Purpose: To develop and evaluate a deep learning model for multi-organ segmentation of MRI scans. Materials and Methods: The model was trained on 1,200 manually annotated 3D axial…
Improve Cross-Modality Segmentation by Treating T1-Weighted MRI Images as Inverted CT Scans
Hartmut Häntze, Lina Xu, Maximilian Rattunde +5
Computed tomography (CT) segmentation models often contain classes that are not currently supported by magnetic resonance imaging (MRI) segmentation models. In this study, we show…
Real-time guidewire tracking and segmentation in intraoperative x-ray
Baochang Zhang, Mai Bui, Cheng Wang +3
During endovascular interventions, physicians have to perform accurate and immediate operations based on the available real-time information, such as the shape and position of guid…