151 citations · 165 across the 13 of their papers we have counts for
13 papers
Auditable agentic AI for evidence-grounded thyroid ultrasound diagnosis and reporting
Haifan Gong, Shiyu Chen, Bodong Wang +11
Thyroid ultrasound diagnosis requires coordinated lesion localization, measurement, risk stratification and reporting, yet most AI systems address these tasks in isolation and prov…
Semantically Calibrated Evidence Composition for CT Vision-Language Learning
Guoliang You, Haifan Gong, Xiaomeng Chu
Learning transferable representations from CT-report pairs requires combining whole-volume context with anatomy-specific evidence. Existing methods typically emphasize either globa…
Learning How Much, Not Just What: Cross-Patient Burden Order for CT Vision-Language Pretraining
Guoliang You, Haifan Gong, Xiaomeng Chu
Volumetric CT vision-language pretraining learns 3D representations from scan-report pairs, but global and anatomy-aware objectives supervise only correspondence: they establish wh…
DreamReg: Belief-Driven World Model for 2D-3D Ultrasound Registration
Luoyao Kang, Yuelin Zhang, Jiwei Shan +3
Ultrasound (US) is widely used for surgical navigation, yet real-time registration between intraoperative 2D slices and preoperative 3D volumes remains challenging due to partial o…
Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models
Haifan Gong, Yitao Wang, Yihan Wang +3
The scarcity and complexity of voxel-level annotations in 3D medical imaging present significant challenges, particularly due to the domain gap between labeled datasets from well-r…
Intensity Confusion Matters: An Intensity-Distance Guided Loss for Bronchus Segmentation
Haifan Gong, Wenhao Huang, Huan Zhang +5
Automatic segmentation of the bronchial tree from CT imaging is important, as it provides structural information for disease diagnosis. Despite the merits of previous automatic bro…
nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model
Haifan Gong, Luoyao Kang, Yitao Wang +2
In the field of biomedical image analysis, the quest for architectures capable of effectively capturing long-range dependencies is paramount, especially when dealing with 3D image…
ASC: Appearance and Structure Consistency for Unsupervised Domain Adaptation in Fetal Brain MRI Segmentation
Zihang Xu, Haifan Gong, Xiang Wan +1
Automatic tissue segmentation of fetal brain images is essential for the quantitative analysis of prenatal neurodevelopment. However, producing voxel-level annotations of fetal bra…
Visual-Attribute Prompt Learning for Progressive Mild Cognitive Impairment Prediction
Luoyao Kang, Haifan Gong, Xiang Wan +1
Deep learning (DL) has been used in the automatic diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) with brain imaging data. However, previous methods have…
Less is More: Adaptive Curriculum Learning for Thyroid Nodule Diagnosis
Haifan Gong, Hui Cheng, Yifan Xie +4
Thyroid nodule classification aims at determining whether the nodule is benign or malignant based on a given ultrasound image. However, the label obtained by the cytological biopsy…
BCNet: Bronchus Classification via Structure Guided Representation Learning
Wenhao Huang, Haifan Gong, Huan Zhang +5
CT-based bronchial tree analysis is essential for diagnosing lung and airway diseases, yet automatic bronchus classification remains challenging because bronchial topology varies s…
A Survey of Natural Language Generation
Chenhe Dong, Yinghui Li, Haifan Gong +4
This paper offers a comprehensive review of the research on Natural Language Generation (NLG) over the past two decades, especially in relation to data-to-text generation and text-…
Cross-Modal Self-Attention with Multi-Task Pre-Training for Medical Visual Question Answering
Haifan Gong, Guanqi Chen, Sishuo Liu +2
Due to the severe lack of labeled data, existing methods of medical visual question answering usually rely on transfer learning to obtain effective image feature representation and…