output
20222025
most citedMetrics reloaded: Recommendations for image analysis validation

469 citations

14 papers

cs.CV2025

Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings

Christian Grashei, Christian Brechenmacher, Rao Muhammad Umer +4

Pathology foundation models (FMs) have driven significant progress in computational pathology. However, these high-performing models can easily exceed a billion parameters and prod…

q-bio.QM2025

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…

cs.CV2025

MultiMAE for Brain MRIs: Robustness to Missing Inputs Using Multi-Modal Masked Autoencoder

Ayhan Can Erdur, Christian Beischl, Daniel Scholz +4

Missing input sequences are common in medical imaging data, posing a challenge for deep learning models reliant on complete input data. In this work, inspired by MultiMAE [2], we d…

cs.RO2025

Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting

Alexander Koebler, Ralf Gross, Florian Buettner +1

Flexible industrial production systems will play a central role in the future of manufacturing due to higher product individualization and customization. A key component in such sy…

eess.IV2025★ 6 cited

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…

eess.IV2024★ 8 cited

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…