18 citations · 49 across the 9 of their papers we have counts for
12 papers
StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors
Qinkai Yu, Chong Zhang, Gaojie Jin +11
Annotating medical data for training AI models is often costly and limited due to the shortage of specialists with relevant clinical expertise. This challenge is further compounded…
A Frequency-Aware Self-Supervised Learning for Ultra-Wide-Field Image Enhancement
Weicheng Liao, Zan Chen, Jianyang Xie +3
Ultra-Wide-Field (UWF) retinal imaging has revolutionized retinal diagnostics by providing a comprehensive view of the retina. However, it often suffers from quality-degrading fact…
GLCP: Global-to-Local Connectivity Preservation for Tubular Structure Segmentation
Feixiang Zhou, Zhuangzhi Gao, He Zhao +5
Accurate segmentation of tubular structures, such as vascular networks, plays a critical role in various medical domains. A remaining significant challenge in this task is structur…
Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transport
Qinkai Yu, Jianyang Xie, Yitian Zhao +7
Multimodal ophthalmic imaging-based diagnosis integrates color fundus image with optical coherence tomography (OCT) to provide a comprehensive view of ocular pathologies. However,…
Parameterized Diffusion Optimization enabled Autoregressive Ordinal Regression for Diabetic Retinopathy Grading
Qinkai Yu, Wei Zhou, Hantao Liu +7
As a long-term complication of diabetes, diabetic retinopathy (DR) progresses slowly, potentially taking years to threaten vision. An accurate and robust evaluation of its severity…
Are Spatial-Temporal Graph Convolution Networks for Human Action Recognition Over-Parameterized?
Jianyang Xie, Yitian Zhao, Yanda Meng +3
Spatial-temporal graph convolutional networks (ST-GCNs) showcase impressive performance in skeleton-based human action recognition (HAR). However, despite the development of numero…
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification
Hongrun Zhang, Yanda Meng, Yitian Zhao +4
Multiple instance learning (MIL) has been increasingly used in the classification of histopathology whole slide images (WSIs). However, MIL approaches for this specific classificat…
3D Dense Face Alignment with Fused Features by Aggregating CNNs and GCNs
Yanda Meng, Xu Chen, Dongxu Gao +5
In this paper, we propose a novel multi-level aggregation network to regress the coordinates of the vertices of a 3D face from a single 2D image in an end-to-end manner. This is ac…
Counting with Adaptive Auxiliary Learning
Yanda Meng, Joshua Bridge, Meng Wei +5
This paper proposes an adaptive auxiliary task learning based approach for object counting problems. Unlike existing auxiliary task learning based methods, we develop an attention-…
BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
Yanda Meng, Hongrun Zhang, Dongxu Gao +5
Segmentation is an essential operation of image processing. The convolution operation suffers from a limited receptive field, while global modelling is fundamental to segmentation…
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
Yanda Meng, Hongrun Zhang, Yitian Zhao +4
Semi-supervised approaches for crowd counting attract attention, as the fully supervised paradigm is expensive and laborious due to its request for a large number of images of dens…
Learning Euler's Elastica Model for Medical Image Segmentation
Xu Chen, Xiangde Luo, Yitian Zhao +3
Image segmentation is a fundamental topic in image processing and has been studied for many decades. Deep learning-based supervised segmentation models have achieved state-of-the-a…