5 papers
Learning latent progression states from spatial heterogeneity in uterine histopathology
Qiming He, Yan Liu, Shuang Ge +20
Tumor progression is accompanied by changes in architecture, morphology and microenvironmental organization, yet progression-associated heterogeneity is usually compressed into sta…
A Digital Pathology Resource for Liver Cancer Quantification with Datasets, Benchmarks, and Tools
Ying Xiao, Shimiao Tang, Xitong Ling +11
Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment directly influence treatment sele…
Leveraging Pre-trained Models for FF-to-FFPE Histopathological Image Translation
Qilai Zhang, Jiawen Li, Peiran Liao +4
The two primary types of Hematoxylin and Eosin (H&E) slides in histopathology are Formalin-Fixed Paraffin-Embedded (FFPE) and Fresh Frozen (FF). FFPE slides offer high quality hist…
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…