11 citations · 18 across the 7 of their papers we have counts for
7 papers
Demonstration of the common dual-channel feature decoupling characteristic of front-door mediation causal inference methods in whole-slice image classification
Zhirui Zhang, Tianhang Nan, Yong Ding +3
Causal inference using front door intervention and multi-instance learning (MIL) has advanced the analysis of Whole Slide Images (WSI) in digital pathology. These methods adjust fe…
Distilling High Diagnostic Value Patches for Whole Slide Image Classification Using Attention Mechanism
Tianhang Nan, Hao Quan, Yong Ding +3
Multiple Instance Learning (MIL) has garnered widespread attention in the field of Whole Slide Image (WSI) classification as it replaces pixel-level manual annotation with diagnost…
Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning
Tianhang Nan, Yong Ding, Hao Quan +4
Due to the lack of fine-grained annotation guidance, current Multiple Instance Learning (MIL) struggles to establish a robust causal relationship between Whole Slide Image (WSI) di…
Dual-channel Prototype Network for few-shot Classification of Pathological Images
Hao Quan, Xinjia Li, Dayu Hu +2
In pathology, the rarity of certain diseases and the complexity in annotating pathological images significantly hinder the creation of extensive, high-quality datasets. This limita…
A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images
Tingting Zheng, Weixing chen, Shuqin Li +7
The deep neural network is a research hotspot for histopathological image analysis, which can improve the efficiency and accuracy of diagnosis for pathologists or be used for disea…
Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners
Hao Quan, Xingyu Li, Weixing Chen +7
Based on digital pathology slice scanning technology, artificial intelligence algorithms represented by deep learning have achieved remarkable results in the field of computational…
Dynamic radiomics: a new methodology to extract quantitative time-related features from tomographic images
Fengying Che, Ruichuan Shi, Jian Wu +6
The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process…