9 papers
Geometry-Aware State Space Model: A New Paradigm for Whole-Slide Image Representation
Enhui Chai, Sicheng Chen, Tianyi Zhang +4
Accurate analysis of histopathological images is critical for disease diagnosis and treatment planning. Whole-slide images (WSIs), which digitize tissue specimens at gigapixel reso…
SegMix:Shuffle-based Feedback Learning for Semantic Segmentation of Pathology Images
Zhiling Yan, Sicheng Chen, Tianyi Zhang +3
Segmentation is a critical task in computational pathology, as it identifies areas affected by disease or abnormal growth and is essential for diagnosis and treatment. However, acq…
MambaBack: Bridging Local Features and Global Contexts in Whole Slide Image Analysis
Sicheng Chen, Chad Wong, Tianyi Zhang +3
Whole Slide Image (WSI) analysis is pivotal in computational pathology, enabling cancer diagnosis by integrating morphological and architectural cues across magnifications. Multipl…
SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification
Enhui Chai, Sicheng Chen, Tianyi Zhang +2
Pathological diagnosis is highly reliant on image analysis, where Regions of Interest (ROIs) serve as the primary basis for diagnostic evidence, while whole-slide image (WSI)-level…
PathRWKV: Enhancing Whole Slide Image Inference with Asymmetric Recurrent Modeling
Tianyi Zhang, Sicheng Chen, Borui Kang +6
Whole Slide Imaging (WSI) has become a gold standard in cancer diagnosis, inspecting multi-scale information from cellular to tissue levels. Processing an entire WSI directly is in…
Federated Cross-Modal Retrieval with Missing Modalities via Semantic Routing and Adapter Personalization
Hefeng Zhou, Xuan Liu, Sicheng Chen +7
Federated cross-modal retrieval faces severe challenges from heterogeneous client data, particularly non-IID semantic distributions and missing modalities. Under such heterogeneity…