21 citations · 38 across the 13 of their papers we have counts for
13 papers
Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation
Changjing Liu, Yiming Huang, Beilei Cui +5
Efficient surgical segmentation empowers clinical diagnosis, intraoperative monitoring, and downstream robotic pipelines for reconstruction and simulation. Although prompt-driven f…
A Chain of Diagnosis Framework for Accurate and Explainable Radiology Report Generation
Haibo Jin, Haoxuan Che, Sunan He +1
Despite the progress of radiology report generation (RRG), existing works face two challenges: 1) The performances in clinical efficacy are unsatisfactory, especially for lesion at…
LLM-driven Medical Report Generation via Communication-efficient Heterogeneous Federated Learning
Haoxuan Che, Haibo Jin, Zhengrui Guo +3
LLMs have demonstrated significant potential in Medical Report Generation (MRG), yet their development requires large amounts of medical image-report pairs, which are commonly scat…
FedDAG: Federated Domain Adversarial Generation Towards Generalizable Medical Image Analysis
Haoxuan Che, Yifei Wu, Haibo Jin +2
Federated domain generalization aims to train a global model from multiple source domains and ensure its generalization ability to unseen target domains. Due to the target domain b…
GameGen-X: Interactive Open-world Game Video Generation
Haoxuan Che, Xuanhua He, Quande Liu +2
We introduce GameGen-X, the first diffusion transformer model specifically designed for both generating and interactively controlling open-world game videos. This model facilitates…
Rethinking Self-training for Semi-supervised Landmark Detection: A Selection-free Approach
Haibo Jin, Haoxuan Che, Hao Chen
Self-training is a simple yet effective method for semi-supervised learning, during which pseudo-label selection plays an important role for handling confirmation bias. Despite its…
Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN
Weiwen Zhang, Dawei Yang, Haoxuan Che +3
For optical coherence tomography angiography (OCTA) images, a limited scanning rate leads to a trade-off between field-of-view (FOV) and imaging resolution. Although larger FOV ima…
Unsupervised Domain Adaptation for Anatomical Landmark Detection
Haibo Jin, Haoxuan Che, Hao Chen
Recently, anatomical landmark detection has achieved great progresses on single-domain data, which usually assumes training and test sets are from the same domain. However, such an…
PromptMRG: Diagnosis-Driven Prompts for Medical Report Generation
Haibo Jin, Haoxuan Che, Yi Lin +1
Automatic medical report generation (MRG) is of great research value as it has the potential to relieve radiologists from the heavy burden of report writing. Despite recent advance…
Towards Generalizable Diabetic Retinopathy Grading in Unseen Domains
Haoxuan Che, Yuhan Cheng, Haibo Jin +1
Diabetic Retinopathy (DR) is a common complication of diabetes and a leading cause of blindness worldwide. Early and accurate grading of its severity is crucial for disease managem…
Image Quality-aware Diagnosis via Meta-knowledge Co-embedding
Haoxuan Che, Siyu Chen, Hao Chen
Medical images usually suffer from image degradation in clinical practice, leading to decreased performance of deep learning-based models. To resolve this problem, most previous wo…
DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images
Bo Qian, Hao Chen, Xiangning Wang +18
Computer-assisted automatic analysis of diabetic retinopathy (DR) is of great importance in reducing the risks of vision loss and even blindness. Ultra-wide optical coherence tomog…
Learning Robust Representation for Joint Grading of Ophthalmic Diseases via Adaptive Curriculum and Feature Disentanglement
Haoxuan Che, Haibo Jin, Hao Chen
Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of permanent blindness worldwide. Designing an automatic grading system with good generalization abili…