Cover Image

Unlocking the Potential of Digital Pathology: Novel Baselines for Compression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fischer, Maximilian, Neher, Peter, Schüffler, Peter, Ziegler, Sebastian, Xiao, Shuhan, Peretzke, Robin, Clunie, David, Ulrich, Constantin, Baumgartner, Michael, Muckenhuber, Alexander, Almeida, Silvia Dias, Götz, Michael, Kleesiek, Jens, Nolden, Marco, Braren, Rickmer, Maier-Hein, Klaus
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
by: Fischer, Maximilian, et al.
Published: (2025)

Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution
by: Fischer, Maximilian, et al.
Published: (2024)

Contrastive virtual staining enhances deep learning‐based PDAC subtyping from H&E‐stained tissue cores
by: Maximilian Fischer, et al.
Published: (2025)

Bridging Radiology and Pathology: A DICOM-Based Framework for Multimodal Mapping and Integrated Visualization
by: Rijhwani, Nilesh P., et al.
Published: (2025)

Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes
by: Fischer, Maximilian, et al.
Published: (2024)

nnLandmark: A Self-Configuring Method for 3D Medical Landmark Detection
by: Ertl, Alexandra, et al.
Published: (2025)

An OpenMind for 3D medical vision self-supervised learning
by: Wald, Tassilo, et al.
Published: (2024)

Temporal Flow Matching for Learning Spatio-Temporal Trajectories in 4D Longitudinal Medical Imaging
by: Disch, Nico Albert, et al.
Published: (2025)

CRONOS: Continuous Time Reconstruction for 4D Medical Longitudinal Series
by: Disch, Nico Albert, et al.
Published: (2025)

MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation
by: Ulrich, Constantin, et al.
Published: (2023)

Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain
by: Bujotzek, Markus R., et al.
Published: (2024)

Data-Centric Strategies for Overcoming PET/CT Heterogeneity: Insights from the AutoPET III Lesion Segmentation Challenge
by: Kovacs, Balint, et al.
Published: (2024)

Mitigating False Predictions In Unreasonable Body Regions
by: Ulrich, Constantin, et al.
Published: (2024)

Kaapana: A Comprehensive Open-Source Platform for Integrating AI in Medical Imaging Research Environments
by: Akünal, Ünal, et al.
Published: (2025)

Multimodal classification of Radiation-Induced Contrast Enhancements and tumor recurrence using deep learning
by: Peretzke, Robin, et al.
Published: (2026)

Input Data Adaptive Learning (IDAL) for Sub-acute Ischemic Stroke Lesion Segmentation
by: Götz, Michael, et al.
Published: (2024)

Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings
by: Grashei, Christian, et al.
Published: (2025)

Self-Supervised Radiograph Anatomical Region Classification -- How Clean Is Your Real-World Data?
by: Langer, Simon, et al.
Published: (2024)

From FDG to PSMA: A Hitchhiker's Guide to Multitracer, Multicenter Lesion Segmentation in PET/CT Imaging
by: Rokuss, Maximilian, et al.
Published: (2024)

Primus: Enforcing Attention Usage for 3D Medical Image Segmentation
by: Wald, Tassilo, et al.
Published: (2025)

nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation
by: Isensee, Fabian, et al.
Published: (2024)

A Hybrid AI-based and Rule-based Approach to DICOM De-identification: A Solution for the MIDI-B Challenge
by: Haghiri, Hamideh, et al.
Published: (2025)

Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration
by: Reithmeir, Anna, et al.
Published: (2024)

Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks
by: Seletkov, Dmitrii, et al.
Published: (2026)

LungEvaty: A Scalable, Open-Source Transformer-based Deep Learning Model for Lung Cancer Risk Prediction in LDCT Screening
by: Brandt, Johannes, et al.
Published: (2025)

MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
by: Roy, Saikat, et al.
Published: (2023)

The Missing Piece: A Case for Pre-Training in 3D Medical Object Detection
by: Eckstein, Katharina, et al.
Published: (2025)

Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures
by: Kirchhoff, Yannick, et al.
Published: (2024)

Overcoming Common Flaws in the Evaluation of Selective Classification Systems
by: Traub, Jeremias, et al.
Published: (2024)

Beyond Knowledge Silos: Task Fingerprinting for Democratization of Medical Imaging AI
by: Godau, Patrick, et al.
Published: (2024)

DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
by: Götz, Michael, et al.
Published: (2024)

Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting
by: Rokuss, Maximilian, et al.
Published: (2024)

Whole-body Representation Learning For Competing Preclinical Disease Risk Assessment
by: Seletkov, Dmitrii, et al.
Published: (2025)

Deep Learning-Based Fixation Type Prediction for Quality Assurance in Digital Pathology
by: Thaeter, Oskar, et al.
Published: (2026)

Decoupling Semantic Similarity from Spatial Alignment for Neural Networks
by: Wald, Tassilo, et al.
Published: (2024)

GRASPing Anatomy to Improve Pathology Segmentation
by: Li, Keyi, et al.
Published: (2025)

On Arbitrary Predictions from Equally Valid Models
by: Lockfisch, Sarah, et al.
Published: (2025)

MedDIFT: Multi-Scale Diffusion-Based Correspondence in 3D Medical Imaging
by: Zhang, Xingyu, et al.
Published: (2025)

Temporal Neural Cellular Automata: Application to modeling of contrast enhancement in breast MRI
by: Lang, Daniel M., et al.
Published: (2025)

Anatomy-guided Pathology Segmentation
by: Jaus, Alexander, et al.
Published: (2024)