4 citations · 9 across the 20 of their papers we have counts for
5 papers · 2 filters
Evaluating Cell AI Foundation Models in Kidney Pathology with Human-in-the-Loop Enrichment
Junlin Guo, Siqi Lu, Can Cui +14
Training AI foundation models has emerged as a promising large-scale learning approach for addressing real-world healthcare challenges, including digital pathology. While many of t…
Large-scale cervical precancerous screening via AI-assisted cytology whole slide image analysis
Honglin Li, Yusuan Sun, Chenglu Zhu +8
Cervical Cancer continues to be the leading gynecological malignancy, posing a persistent threat to women's health on a global scale. Early screening via cytology Whole Slide Image…
PFPs: Prompt-guided Flexible Pathological Segmentation for Diverse Potential Outcomes Using Large Vision and Language Models
Can Cui, Ruining Deng, Junlin Guo +4
The Vision Foundation Model has recently gained attention in medical image analysis. Its zero-shot learning capabilities accelerate AI deployment and enhance the generalizability o…
mTREE: Multi-Level Text-Guided Representation End-to-End Learning for Whole Slide Image Analysis
Quan Liu, Ruining Deng, Can Cui +4
Multi-modal learning adeptly integrates visual and textual data, but its application to histopathology image and text analysis remains challenging, particularly with large, high-re…
Nucleus subtype classification using inter-modality learning
Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios +14
Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available b…