4 papers · 1 filter
Diagnostic Text-guided Representation Learning in Hierarchical Classification for Pathological Whole Slide Image
Jiawen Li, Qiehe Sun, Renao Yan +7
With the development of digital imaging in medical microscopy, artificial intelligent-based analysis of pathological whole slide images (WSIs) provides a powerful tool for cancer d…
Task-oriented Embedding Counts: Heuristic Clustering-driven Feature Fine-tuning for Whole Slide Image Classification
Xuenian Wang, Shanshan Shi, Renao Yan +4
In the field of whole slide image (WSI) classification, multiple instance learning (MIL) serves as a promising approach, commonly decoupled into feature extraction and aggregation.…
RetMIL: Retentive Multiple Instance Learning for Histopathological Whole Slide Image Classification
Hongbo Chu, Qiehe Sun, Jiawen Li +5
Histopathological whole slide image (WSI) analysis with deep learning has become a research focus in computational pathology. The current paradigm is mainly based on multiple insta…
Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image Analysis
Jiawen Li, Yuxuan Chen, Hongbo Chu +4
Histopathological whole slide images (WSIs) classification has become a foundation task in medical microscopic imaging processing. Prevailing approaches involve learning WSIs as in…