activity
20212025
most citedProSFDA: Prompt Learning based Source-free Domain Adaptation for Medical Image Segmentation

11 citations · 19 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2023

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…

cs.CV2023★ 1 cited

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…

cs.CV2022

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…

cs.CV2022★ 11 cited

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…

eess.IV2022★ 1 cited

Boundary-Aware Network for Abdominal Multi-Organ Segmentation

Shishuai Hu, Zehui Liao, Yong Xia

Automated abdominal multi-organ segmentation is a crucial yet challenging task in the computer-aided diagnosis of abdominal organ-related diseases. Although numerous deep learning…

eess.IV2022

Boundary-Aware Network for Kidney Parsing

Shishuai Hu, Yiwen Ye, Zehui Liao +1

Kidney structures segmentation is a crucial yet challenging task in the computer-aided diagnosis of surgery-based renal cancer. Although numerous deep learning models have achieved…

eess.IV2022★ 3 cited

Label Propagation for 3D Carotid Vessel Wall Segmentation and Atherosclerosis Diagnosis

Shishuai Hu, Zehui Liao, Yong Xia

Carotid vessel wall segmentation is a crucial yet challenging task in the computer-aided diagnosis of atherosclerosis. Although numerous deep learning models have achieved remarkab…

cs.CV2021★ 2 cited

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…

eess.IV2021

Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image Segmentation

Shishuai Hu, Zehui Liao, Jianpeng Zhang +1

The domain gap caused mainly by variable medical image quality renders a major obstacle on the path between training a segmentation model in the lab and applying the trained model…

eess.IV2021★ 1 cited

Learning from Ambiguous Labels for Lung Nodule Malignancy Prediction

Zehui Liao, Yutong Xie, Shishuai Hu +1

Lung nodule malignancy prediction is an essential step in the early diagnosis of lung cancer. Besides the difficulties commonly discussed, the challenges of this task also come fro…