4 papers
PathAR: Structure-First Autoregressive Synthesis of Multimodal Pathology Images
Yuan Zhang, Jiahao Xia, Junzhang Huang +4
Data scarcity in multimodal pathology motivates unified generative models that synthesize modality-specific appearance while preserving anatomically coherent structure. Although mo…
PathFL: Multi-Alignment Federated Learning for Pathology Image Segmentation
Yuan Zhang, Feng Chen, Yaolei Qi +2
Pathology image segmentation across multiple centers encounters significant challenges due to diverse sources of heterogeneity including imaging modalities, organs, and scanning eq…
Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
Yuan Zhang, Xinfeng Zhang, Xiaoming Qi +4
Content generation modeling has emerged as a promising direction in computational pathology, offering capabilities such as data-efficient learning, synthetic data augmentation, and…
FedSODA: Federated Cross-assessment and Dynamic Aggregation for Histopathology Segmentation
Yuan Zhang, Yaolei Qi, Xiaoming Qi +4
Federated learning (FL) for histopathology image segmentation involving multiple medical sites plays a crucial role in advancing the field of accurate disease diagnosis and treatme…