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Showing 551–575 of 745 papers

TitleStatusHype
Ultra-Resolution Cascaded Diffusion Model for Gigapixel Image Synthesis in Histopathology—0
UNICORN: A Deep Learning Model for Integrating Multi-Stain Data in Histopathology—0
Unleashing the Infinity Power of Geometry: A Novel Geometry-Aware Transformer (GOAT) for Whole Slide Histopathology Image Analysis—0
Unlocking the Potential of Digital Pathology: Novel Baselines for Compression—0
Unsupervised Artifact Detection for Whole Slide Images of Prostate Biopsies—0
Unsupervised Latent Stain Adaptation for Computational Pathology—0
Unsupervised Learning of Deep-Learned Features from Breast Cancer Images—0
Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification—0
Using deep learning to detect patients at risk for prostate cancer despite benign biopsies—0
Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression—0
UWarp: A Whole Slide Image Registration Pipeline to Characterize Scanner-Induced Local Domain Shift—0
Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology—0
Vision Transformer-Based Deep Learning for Histologic Classification of Endometrial Cancer—0
Visual attention analysis of pathologists examining whole slide images of Prostate cancer—0
Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer—0
Weakly supervised training of pixel resolution segmentation models on whole slide images—0
WeakSTIL: Weak whole-slide image level stromal tumor infiltrating lymphocyte scores are all you need—0
Weighted multi-level deep learning analysis and framework for processing breast cancer WSIs—0
What a Whole Slide Image Can Tell? Subtype-guided Masked Transformer for Pathological Image Captioning—0
When an Image is Worth 1,024 x 1,024 Words: A Case Study in Computational Pathology—0
Whole Slide Image Classification of Salivary Gland Tumours—0
Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection—0
Whole slide image registration for the study of tumor heterogeneity—0
Comparing ImageNet Pre-training with Digital Pathology Foundation Models for Whole Slide Image-Based Survival Analysis—0
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks—0
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