most citedCross-modal Diffusion Modelling for Super-resolved Spatial Transcriptomics

1 citations · 1 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2025

C3-Diff: Super-resolving Spatial Transcriptomics via Cross-modal Cross-content Contrastive Diffusion Modelling

Xiaofei Wang, Stephen Price, Chao Li

The rapid advancement of spatial transcriptomics (ST), i.e., spatial gene expressions, has made it possible to measure gene expression within original tissue, enabling us to discov…

eess.IV2025

Disentangled Multi-modal Learning of Histology and Transcriptomics for Cancer Characterization

Yupei Zhang, Xiaofei Wang, Anran Liu +2

Histopathology remains the gold standard for cancer diagnosis and prognosis. With the advent of transcriptome profiling, multi-modal learning combining transcriptomics with histolo…

eess.IV2025

Score-based Diffusion Model for Unpaired Virtual Histology Staining

Anran Liu, Xiaofei Wang, Jing Cai +1

Hematoxylin and eosin (H&E) staining visualizes histology but lacks specificity for diagnostic markers. Immunohistochemistry (IHC) staining provides protein-targeted staining but i…

eess.IV2025

Adaptive Spatial Transcriptomics Interpolation via Cross-modal Cross-slice Modeling

NingFeng Que, Xiaofei Wang, Jingjing Chen +2

Spatial transcriptomics (ST) is a promising technique that characterizes the spatial gene profiling patterns within the tissue context. Comprehensive ST analysis depends on consecu…

cs.CV2025

Joint Modelling Histology and Molecular Markers for Cancer Classification

Xiaofei Wang, Hanyu Liu, Yupei Zhang +6

Cancers are characterized by remarkable heterogeneity and diverse prognosis. Accurate cancer classification is essential for patient stratification and clinical decision-making. Al…

eess.IV2024

Knowledge-driven Subspace Fusion and Gradient Coordination for Multi-modal Learning

Yupei Zhang, Xiaofei Wang, Fangliangzi Meng +2

Multi-modal learning plays a crucial role in cancer diagnosis and prognosis. Current deep learning based multi-modal approaches are often limited by their abilities to model the co…

cs.CV2024

Unified Modeling Enhanced Multimodal Learning for Precision Neuro-Oncology

Huahui Yi, Xiaofei Wang, Kang Li +1

Multimodal learning, integrating histology images and genomics, promises to enhance precision oncology with comprehensive views at microscopic and molecular levels. However, existi…

cs.CV2024

Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation

Hao Chen, Hongrun Zhang, U Wang Chan +3

Single domain generalization aims to address the challenge of out-of-distribution generalization problem with only one source domain available. Feature distanglement is a classic s…

eess.IV2024★ 1 cited

Cross-modal Diffusion Modelling for Super-resolved Spatial Transcriptomics

Xiaofei Wang, Xingxu Huang, Stephen J. Price +1

The recent advancement of spatial transcriptomics (ST) allows to characterize spatial gene expression within tissue for discovery research. However, current ST platforms suffer fro…