5 papers
Understanding Synergistic Interactions among Pathology Foundation Models via Adaptive Fusion
Yuxiang Xiao, Yang Hu, Bin Li +5
Pathology foundation models (PFMs) provide strong tile-level representations via self-supervised pre-training on large-scale pathology images. Yet, PFMs are developed under diverse…
Harnessing Adversarial Distillation to Customise Debiased, Disease-Specific Pathology Foundation Models for Breast Cancer
Zhiwei Chen, Yang Hu, Yuxiang Xiao +7
Pathology foundation models (PFMs) provide strong tissue representations and have become central to digital pathology. However, deployment in disease-specific settings is limited b…
TraceTrans: Translation and Spatial Tracing for Surgical Prediction
Xiyu Luo, Haodong Li, Xinxing Cheng +4
Image-to-image translation models have achieved notable success in converting images across visual domains and are increasingly used for medical tasks such as predicting post-opera…
AdaFusion: Prompt-Guided Inference with Adaptive Fusion of Pathology Foundation Models
Yuxiang Xiao, Yang Hu, Bin Li +5
Pathology foundation models (PFMs) have demonstrated strong representational capabilities through self-supervised pre-training on large-scale, unannotated histopathology image data…
Structure Unbiased Adversarial Model for Medical Image Segmentation
Tianyang Zhang, Shaoming Zheng, Jun Cheng +7
Generative models have been widely proposed in image recognition to generate more images where the distribution is similar to that of the real ones. It often introduces a discrimin…