8 citations · 15 across the 10 of their papers we have counts for
12 papers
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
Federated Medical Image Segmentation under Real-World Label Noise: A Benchmark Suite for Noisy Label Learning Method Selection
Markus Bujotzek, Dimitrios Bounias, Stefan Denner +4
While federated learning (FL) enables collaborative medical image segmentation without centralizing sensitive data, real-world deployment is frequently complicated by cross-site la…
Bridging Radiology and Pathology: A DICOM-Based Framework for Multimodal Mapping and Integrated Visualization
Nilesh P. Rijhwani, Titus J. Brinker, Peter Neher +4
Accurate disease diagnosis depends on effective collaboration between medical specialties, yet departments often use distinct data systems and proprietary formats. This heterogenei…
Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge
Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47
The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…
nnLandmark: A Self-Configuring Method for 3D Medical Landmark Detection
Alexandra Ertl, Stefan Denner, Robin Peretzke +8
Landmark detection is central to many medical applications, such as identifying critical structures for treatment planning or defining control points for biometric measurements. Ho…
Multimedia and Visual Analytics in the Agentic Era
Marcel Worring, Jan Zahálka, Stef van den Elzen +2
Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have rapidly changed the playing field, and i…
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
Maximilian Fischer, Peter Neher, Peter Schüffler +9
Accurate diagnosis of disease often depends on the exhaustive examination of Whole Slide Images (WSI) at microscopic resolution. Efficient handling of these data-intensive images r…
KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level
Ruining Deng, Tianyuan Yao, Yucheng Tang +44
Chronic kidney disease (CKD) is a major global health issue, affecting over 10% of the population and causing significant mortality. While kidney biopsy remains the gold standard f…
Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes
Maximilian Fischer, Florian M. Hauptmann, Robin Peretzke +4
Although advances in brain surgery techniques have led to fewer postoperative complications requiring Intensive Care Unit (ICU) monitoring, the routine transfer of patients to the…
Unlocking the Potential of Digital Pathology: Novel Baselines for Compression
Maximilian Fischer, Peter Neher, Peter Schüffler +13
Digital pathology offers a groundbreaking opportunity to transform clinical practice in histopathological image analysis, yet faces a significant hurdle: the substantial file sizes…
Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution
Maximilian Fischer, Peter Neher, Tassilo Wald +9
Processing histopathological Whole Slide Images (WSI) leads to massive storage requirements for clinics worldwide. Even after lossy image compression during image acquisition, addi…
Mitigating False Predictions In Unreasonable Body Regions
Constantin Ulrich, Catherine Knobloch, Julius C. Holzschuh +7
Despite considerable strides in developing deep learning models for 3D medical image segmentation, the challenge of effectively generalizing across diverse image distributions pers…