9.8k citations
- Heidelberg UniversityDE148 papers
- University Hospital HeidelbergDE68 papers
- National Center for Tumor DiseasesDE29 papers
- DKFZ-ZMBH AllianceDE21 papers
- Deutsches Konsortium für Translationale KrebsforschungDE20 papers
- Technical University of MunichDE19 papers
- University Hospital Carl Gustav CarusDE19 papers
- Technische Universität DresdenDE18 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE17 papers
- Harvard UniversityUS15 papers
- King's College LondonGB14 papers
- University College LondonGB14 papers
219 papers
Performance uncertainty in medical image analysis: a large-scale investigation of confidence intervals
Pascaline André, Charles Heitz, Evangelia Christodoulou +10
Performance uncertainty quantification is essential for reliable validation and eventual clinical translation of medical imaging artificial intelligence (AI). Confidence intervals…
In search of truth: Evaluating concordance of AI-based anatomy segmentation models
Lena Giebeler, Deepa Krishnaswamy, David Clunie +9
Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the cha…
Efficient Optimization of a Permanent Magnet Array for a Stable 2D Trap
Ann-Sophia Müller, Moonkwang Jeong, Jiyuan Tian +2
Untethered magnetic manipulation of biomedical millirobots has a high potential for minimally invasive surgical applications. However, it is still challenging to exert high actuati…
Gut decisions based on the liver: A radiomics approach to boost colorectal cancer screening
Anna Hinterberger, Jonas Bohn, Dasha Trofimova +13
Non-invasive colorectal cancer (CRC) screening represents a key opportunity to improve colonoscopy participation rates and reduce CRC mortality. This study explores the potential o…
Transformer-Based Hematological Malignancy Prediction from Peripheral Blood Smears in a Real-World Cohort
Muhammed Furkan Dasdelen, Ivan Kukuljan, Peter Lienemann +6
Peripheral blood smears remain a cornerstone in the diagnosis of hematological neoplasms, offering rapid and valuable insights that inform subsequent diagnostic steps. However, sin…
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16
Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…