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most citedUnlocking the Potential of Digital Pathology: Novel Baselines for Compression

8 citations · 15 across the 10 of their papers we have counts for

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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

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…

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…

eess.IV2024★ 1 cited

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…

eess.IV2024

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…