5 papers
CellPlex: Benchmarking Single-Cell Spatial Proteomics Prediction from H&E
Zijun Gao, Yijiang Chen, Xiangde Luo +1
Spatial proteomics measures tens of proteins in every cell of a tissue section, but its cost confines it to small research cohorts, whereas hematoxylin and eosin (H\&E) slides exis…
Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images
Zijun Gao, Chunbin Gu, Jinxi Xiang +2
Predicting gene expression from H&E-stained histology images offers a scalable alternative to costly spatial transcriptomics, yet most existing methods operate at the spot level, w…
Bi-TEAM: A Unified Cross-Scale Representation Learning Framework for Chemically Modified Biomolecules
Chunbin Gu, Zijun Gao, Mutian He +8
Representation learning for protein biochemical space faces a difficult trade-off: protein language models excel at capturing long-range biological semantics but often miss fine-gr…
Dynamic Gradient Sparsification Training for Few-Shot Fine-tuning of CT Lymph Node Segmentation Foundation Model
Zihao Luo, Zijun Gao, Wenjun Liao +3
Accurate lymph node (LN) segmentation is critical in radiotherapy treatment and prognosis analysis, but is limited by the need for large annotated datasets. While deep learning-bas…
An Uncertainty-guided Tiered Self-training Framework for Active Source-free Domain Adaptation in Prostate Segmentation
Zihao Luo, Xiangde Luo, Zijun Gao +1
Deep learning models have exhibited remarkable efficacy in accurately delineating the prostate for diagnosis and treatment of prostate diseases, but challenges persist in achieving…