4 citations · 4 across the 6 of their papers we have counts for
6 papers
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images
Liangrui Pan, Lian Wang, Zhichao Feng +2
Histopathology image segmentation is the gold standard for diagnosing cancer, and can indicate cancer prognosis. However, histopathology image segmentation requires high-quality ma…
LDCSF: Local depth convolution-based Swim framework for classifying multi-label histopathology images
Liangrui Pan, Yutao Dou, Zhichao Feng +2
Histopathological images are the gold standard for diagnosing liver cancer. However, the accuracy of fully digital diagnosis in computational pathology needs to be improved. In thi…
MGTUNet: An new UNet for colon nuclei instance segmentation and quantification
Liangrui Pan, Lian Wang, Zhichao Feng +3
Colorectal cancer (CRC) is among the top three malignant tumor types in terms of morbidity and mortality. Histopathological images are the gold standard for diagnosing colon cancer…
A review of machine learning approaches, challenges and prospects for computational tumor pathology
Liangrui Pan, Zhichao Feng, Shaoliang Peng
Computational pathology is part of precision oncology medicine. The integration of high-throughput data including genomics, transcriptomics, proteomics, metabolomics, pathomics, an…
Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma
Liangrui Pan, Hetian Wang, Lian Wang +5
The degree of malignancy of osteosarcoma and its tendency to metastasize/spread mainly depend on the pathological grade (determined by observing the morphology of the tumor under a…
Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery
Xiaoqi Wang, Yingjie Cheng, Yaning Yang +3
Self-supervised representation learning (SSL) on biomedical networks provides new opportunities for drug discovery. However, how to effectively combine multiple SSL models is still…