11 citations · 19 across the 14 of their papers we have counts for
9 papers · 1 filter
Cycle Context Verification for In-Context Medical Image Segmentation
Shishuai Hu, Zehui Liao, Liangli Zhen +2
In-context learning (ICL) is emerging as a promising technique for achieving universal medical image segmentation, where a variety of objects of interest across imaging modalities…
UniVRSE: Unified Vision-conditioned Response Semantic Entropy for Hallucination Detection in Medical Vision-Language Models
Zehui Liao, Shishuai Hu, Ke Zou +5
Vision-language models (VLMs) have great potential for medical image understanding, particularly in Visual Report Generation (VRG) and Visual Question Answering (VQA), but they may…
Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification
Zehui Liao, Shishuai Hu, Yanning Zhang +1
Addressing mixed closed-set and open-set label noise in medical image classification remains a largely unexplored challenge. Unlike natural image classification, which often separa…
Towards Clinician-Preferred Segmentation: Leveraging Human-in-the-Loop for Test Time Adaptation in Medical Image Segmentation
Shishuai Hu, Zehui Liao, Zeyou Liu +1
Deep learning-based medical image segmentation models often face performance degradation when deployed across various medical centers, largely due to the discrepancies in data dist…
Transformer-based Annotation Bias-aware Medical Image Segmentation
Zehui Liao, Yutong Xie, Shishuai Hu +1
Manual medical image segmentation is subjective and suffers from annotator-related bias, which can be mimicked or amplified by deep learning methods. Recently, researchers have sug…
Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation
Shishuai Hu, Zehui Liao, Yong Xia
Deep learning-based medical image segmentation models suffer from performance degradation when deployed to a new healthcare center. To address this issue, unsupervised domain adapt…
Instance-dependent Label Distribution Estimation for Learning with Label Noise
Zehui Liao, Shishuai Hu, Yutong Xie +1
Noise transition matrix (NTM) estimation is a promising approach for learning with label noise. It can infer clean posterior probabilities, known as Label Distribution (LD), based…
ProSFDA: Prompt Learning based Source-free Domain Adaptation for Medical Image Segmentation
Shishuai Hu, Zehui Liao, Yong Xia
The domain discrepancy existed between medical images acquired in different situations renders a major hurdle in deploying pre-trained medical image segmentation models for clinica…
Modeling Annotator Preference and Stochastic Annotation Error for Medical Image Segmentation
Zehui Liao, Shishuai Hu, Yutong Xie +1
Manual annotation of medical images is highly subjective, leading to inevitable and huge annotation biases. Deep learning models may surpass human performance on a variety of tasks…