5 papers
HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification
Cheng Jin, Luyang Luo, Huangjing Lin +2
Fine-grained classification of whole slide images (WSIs) is essential in precision oncology, enabling precise cancer diagnosis and personalized treatment strategies. The core of th…
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model
Yingxue Xu, Yihui Wang, Fengtao Zhou +16
Remarkable strides in computational pathology have been made in the task-agnostic foundation model that advances the performance of a wide array of downstream clinical tasks. Despi…
Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation
Hao Jiang, Cheng Jin, Huangjing Lin +15
Cervical cancer is a leading malignancy in female reproductive system. While AI-assisted cytology offers a cost-effective and non-invasive screening solution, current systems strug…
GAInS: Gradient Anomaly-aware Biomedical Instance Segmentation
Runsheng Liu, Hao Jiang, Yanning Zhou +3
Instance segmentation plays a vital role in the morphological quantification of biomedical entities such as tissues and cells, enabling precise identification and delineation of di…
Holistic and Historical Instance Comparison for Cervical Cell Detection
Hao Jiang, Runsheng Liu, Yanning Zhou +2
Cytology screening from Papanicolaou (Pap) smears is a common and effective tool for the preventive clinical management of cervical cancer, where abnormal cell detection from whole…