7 papers
Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks
Santhosh Parampottupadam, Andres Martinez, Dimitrios Bounias +3
The paper measures how much patient information can be reconstructed from model gradients in federated learning of radiology reports, comparing three different tokenizers and showi…
TwinTrack: Post-hoc Multi-Rater Calibration for Medical Image Segmentation
Tristan Kirscher, Alexandra Ertl, Klaus Maier-Hein +3
Pancreatic ductal adenocarcinoma (PDAC) segmentation on contrast-enhanced CT is inherently ambiguous: inter-rater disagreement among experts reflects genuine uncertainty rather tha…
Beyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videos
Jieyun Bai, Zihao Zhou, Yitong Tang +60
A substantial proportion (45\%) of maternal deaths, neonatal deaths, and stillbirths occur during the intrapartum phase, with a particularly high burden in low- and middle-income c…
Kaapana: A Comprehensive Open-Source Platform for Integrating AI in Medical Imaging Research Environments
Ãnal Akünal, Markus Bujotzek, Stefan Denner +8
Developing generalizable AI for medical imaging requires both access to large, multi-center datasets and standardized, reproducible tooling within research environments. However, l…
Medical Image De-Identification Benchmark Challenge
Linmin Pei, Granger Sutton, Michael Rutherford +67
The de-identification (deID) of protected health information (PHI) and personally identifiable information (PII) is a fundamental requirement for sharing medical images, particular…
Visual Prompt Engineering for Vision Language Models in Radiology
Stefan Denner, Markus Bujotzek, Dimitrios Bounias +3
Medical image classification plays a crucial role in clinical decision-making, yet most models are constrained to a fixed set of predefined classes, limiting their adaptability to…