76 citations · 151 across the 18 of their papers we have counts for
5 papers · 1 filter
Reducing Domain Gap in Frequency and Spatial domain for Cross-modality Domain Adaptation on Medical Image Segmentation
Shaolei Liu, Siqi Yin, Linhao Qu +1
Unsupervised domain adaptation (UDA) aims to learn a model trained on source domain and performs well on unlabeled target domain. In medical image segmentation field, most existing…
Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classification
Linhao Qu, Xiaoyuan Luo, Manning Wang +1
Computer-aided pathology diagnosis based on the classification of Whole Slide Image (WSI) plays an important role in clinical practice, and it is often formulated as a weakly-super…
Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis
Linhao Qu, Siyu Liu, Xiaoyu Liu +2
Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of p…
DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification
Linhao Qu, Xiaoyuan Luo, Shaolei Liu +2
Multiple Instance Learning (MIL) is widely used in analyzing histopathological Whole Slide Images (WSIs). However, existing MIL methods do not explicitly model the data distributio…
TransFuse: A Unified Transformer-based Image Fusion Framework using Self-supervised Learning
Linhao Qu, Shaolei Liu, Manning Wang +4
Image fusion is a technique to integrate information from multiple source images with complementary information to improve the richness of a single image. Due to insufficient task-…