176 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of LübeckDE21 papers
- Hamburg University of TechnologyDE7 papers
- Christian-Albrechts-Universität zu KielDE5 papers
- Universität HamburgDE3 papers
- Comprehensive Cancer Center ErlangenDE2 papers
- German Cancer Research CenterDE2 papers
- German Centre for Cardiovascular ResearchDE2 papers
- Heidelberg UniversityDE2 papers
- Humboldt-Universität zu BerlinDE2 papers
- Karlsruhe Institute of TechnologyDE2 papers
- LMU KlinikumDE2 papers
- Ludwig-Maximilians-Universität MünchenDE2 papers
5 papers · 1 filter
FedSynthCT-Brain: A Federated Learning Framework for Multi-Institutional Brain MRI-to-CT Synthesis
Ciro Benito Raggio, Mathias Krohmer Zabaleta, Nils Skupien +6
The generation of Synthetic Computed Tomography (sCT) images has become a pivotal methodology in modern clinical practice, particularly in the context of Radiotherapy (RT) treatmen…
Clinical Melanoma Diagnosis with Artificial Intelligence: Insights from a Prospective Multicenter Study
Lukas Heinlein, Roman C. Maron, Achim Hekler +27
Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence…
Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study
Achim Hekler, Roman C. Maron, Sarah Haggenmüller +28
Background: Convolutional neural network (CNN)-based melanoma classifiers face several challenges that limit their usefulness in clinical practice. Objective: To investigate the im…
Spatio-Temporal Deep Learning Models for Tip Force Estimation During Needle Insertion
Nils Gessert, Torben Priegnitz, Thore Saathoff +6
Purpose. Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and…
An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT
Stefan Reinhold. Timo Damm, Lukas Huber, Reimer Andresen +3
Quantitative computed tomography (QCT) is a widely used tool for osteoporosis diagnosis and monitoring. The assessment of cortical markers like cortical bone mineral density (BMD)…