6 papers
STAMP: Multi-pattern Attention-aware Multiple Instance Learning for STAS Diagnosis in Multi-center Histopathology Images
Liangrui Pan, xiaoyu Li, Guang Zhu +6
Spread through air spaces (STAS) constitutes a novel invasive pattern in lung adenocarcinoma (LUAD), associated with tumor recurrence and diminished survival rates. However, large-…
PathGene: Benchmarking Driver Gene Mutations and Exon Prediction Using Multicenter Lung Cancer Histopathology Image Dataset
Liangrui Pan, Qingchun Liang, Shen Zhao +2
Accurately predicting gene mutations, mutation subtypes and their exons in lung cancer is critical for personalized treatment planning and prognostic assessment. Faced with regiona…
DLiPath: A Benchmark for the Comprehensive Assessment of Donor Liver Based on Histopathological Image Dataset
Liangrui Pan, Xingchen Li, Zhongyi Chen +2
Pathologists comprehensive evaluation of donor liver biopsies provides crucial information for accepting or discarding potential grafts. However, rapidly and accurately obtaining t…
SMILE: a Scale-aware Multiple Instance Learning Method for Multicenter STAS Lung Cancer Histopathology Diagnosis
Liangrui Pan, Xiaoyu Li, Yutao Dou +4
Spread through air spaces (STAS) represents a newly identified aggressive pattern in lung cancer, which is known to be associated with adverse prognostic factors and complex pathol…
Feature-interactive Siamese graph encoder-based image analysis to predict STAS from histopathology images in lung cancer
Liangrui Pan, Qingchun Liang, Wenwu Zeng +6
Spread through air spaces (STAS) is a distinct invasion pattern in lung cancer, crucial for prognosis assessment and guiding surgical decisions. Histopathology is the gold standard…
FedDP: Privacy-preserving method based on federated learning for histopathology image segmentation
Liangrui Pan, Mao Huang, Lian Wang +2
Hematoxylin and Eosin (H&E) staining of whole slide images (WSIs) is considered the gold standard for pathologists and medical practitioners for tumor diagnosis, surgical planning,…