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Found 6 papers, 5 papers with code
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images
Whole slide image (WSI) analysis presents significant computational challenges due to the massive number of patches in gigapixel images.
FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification
To this end, we introduce the knowledge-enhanced adaptive visual compression framework, dubbed FOCUS, which uniquely combines pathology FMs with language prior knowledge to enable a focused analysis of diagnostically relevant regions by prioritizing discriminative WSI patches.
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation
To this end, we propose BLEND, the behavior-guided neural population dynamics modeling framework via privileged knowledge distillation.
Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation
To address this gap, we established a most comprehensive benchmark to evaluate the performance of off-the-shelf foundation models across six distinct clinical task types, encompassing a total of 39 specific tasks.
HistGen: Histopathology Report Generation via Local-Global Feature Encoding and Cross-modal Context Interaction
Histopathology serves as the gold standard in cancer diagnosis, with clinical reports being vital in interpreting and understanding this process, guiding cancer treatment and patient care.
Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions
Thus, label-efficient deep learning methods are developed to make comprehensive use of the labeled data as well as the abundance of unlabeled and weak-labeled data.
