502 citations · 561 across the 49 of their papers we have counts for
51 papers
AWR-Net: Decoupling Anatomy and Appearance for 3D Fetal Brain Ultrasound Synthesis
Yuhuan Lu, Sergio Valencia, Yuanji Zhang +4
Three-dimensional fetal brain ultrasound offers non-ionizing, cost-effective imaging with rich spatial information for comprehensive anatomical assessment, yet its development rema…
Deep Learning-based Intelligent Diagnosis of Congenital Uterine Anomalies in 3D Ultrasound
Yueyue Xu, Yuhao Huang, Jiaxiao Deng +11
Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requiring coronal plane reconstructio…
Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening
Yuhao Huang, Yuanji Zhang, Yuhuan Lu +3
Assessment of ventriculomegaly (VM) on fetal brain ultrasound relies primarily on measuring lateral ventricular atrial width on standard planes, which is operator-dependent and may…
Rethinking Medical Landmark Localization with Prototype Learning-based Progressive Offset Correction
Jingxian Xu, Yuhao Huang, Rusi Chen +2
Accurate landmark localization in medical images is a fundamental step for quantitative clinical measurement and downstream analysis. Existing localization methods have advanced, a…
Recurrent Contrastive Learning for Imbalanced Medical Image Classification
Zhiyuan Zhu, Xinling Meng, Junxuan Yu +15
Medical image classification often suffers from class imbalance due to the inherent disparities in disease incidence. Existing approaches, such as class resampling and loss reweigh…
ClinRAG-GRAPH: Clinical-prior Retrieval-Augmented Graph Model with Domain Adversarial Learning for Breast pCR Prediction
Yaofei Duan, Yuhao Huang, Tianyu Zhang +12
Neoadjuvant chemotherapy (NAC) response prediction is clinically important for treatment stratification in breast cancer. However, robust pre-treatment pathological complete respon…
FrameONE: Hierarchical Motion Modeling for Universal Multi-View Echocardiographic Keyframe Detection
Rusi Chen, Yuhao Huang, Hongyuan Zhang +4
Accurate detection of end-systole (ES) and end-diastole (ED) frames is fundamental to echocardiographic assessment. Existing methods are typically developed in a view-specific mann…
Foundation Model-driven Key Anatomy Frame Selection for Blind-sweep Ultrasound Fetal Birth Weight Estimation
Le Ou, Xiliang Zhu, Huanwen Liang +8
Accurate fetal birth weight (FBW) estimation shortly before delivery is clinically valuable yet challenging due to its reliance on operator expertise, particularly in low-resource…
Prototype Memory-Guided Training-Free Anomaly Classification and Localization in Prenatal Ultrasound
Huanwen Liang, Yuhao Huang, Xiliang Zhu +6
Prenatal anomaly classification and localization is of critical importance for fetal health and pregnancy management. Although ultrasound (US) is the primary modality for prenatal…
Artificial Intelligence for Detecting Fetal Orofacial Clefts and Advancing Medical Education
Yuanji Zhang, Yuhao Huang, Haoran Dou +28
Orofacial clefts are among the most common congenital craniofacial abnormalities, yet accurate prenatal detection remains challenging due to the scarcity of experienced specialists…
Subtyping Breast Lesions via Generative Augmentation based Long-tailed Recognition in Ultrasound
Shijing Chen, Xinrui Zhou, Yuhao Wang +4
Accurate identification of breast lesion subtypes can facilitate personalized treatment and interventions. Ultrasound (US), as a safe and accessible imaging modality, is extensivel…
MTCNet: Motion and Topology Consistency Guided Learning for Mitral Valve Segmentationin 4D Ultrasound
Rusi Chen, Yuanting Yang, Jiezhi Yao +12
Mitral regurgitation is one of the most prevalent cardiac disorders. Four-dimensional (4D) ultrasound has emerged as the primary imaging modality for assessing dynamic valvular mor…
Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound
Huanwen Liang, Jingxian Xu, Yuanji Zhang +11
Fetal abdominal malformations are serious congenital anomalies that require accurate diagnosis to guide pregnancy management and reduce mortality. Although AI has demonstrated sign…
ADAptation: Reconstruction-based Unsupervised Active Learning for Breast Ultrasound Diagnosis
Yaofei Duan, Yuhao Huang, Xin Yang +9
Deep learning-based diagnostic models often suffer performance drops due to distribution shifts between training (source) and test (target) domains. Collecting and labeling suffici…
MReg: A Novel Regression Model with MoE-based Video Feature Mining for Mitral Regurgitation Diagnosis
Zhe Liu, Yuhao Huang, Lian Liu +9
Color Doppler echocardiography is a crucial tool for diagnosing mitral regurgitation (MR). Recent studies have explored intelligent methods for MR diagnosis to minimize user depend…
UltraTwin: Towards Cardiac Anatomical Twin Generation from Multi-view 2D Ultrasound
Junxuan Yu, Yaofei Duan, Yuhao Huang +22
Echocardiography is routine for cardiac examination. However, 2D ultrasound (US) struggles with accurate metric calculation and direct observation of 3D cardiac structures. Moreove…
Hierarchical Corpus-View-Category Refinement for Carotid Plaque Risk Grading in Ultrasound
Zhiyuan Zhu, Jian Wang, Yong Jiang +10
Accurate carotid plaque grading (CPG) is vital to assess the risk of cardiovascular and cerebrovascular diseases. Due to the small size and high intra-class variability of plaque,…
Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound
Yuhao Huang, Yueyue Xu, Haoran Dou +4
Congenital uterine anomalies (CUAs) can lead to infertility, miscarriage, preterm birth, and an increased risk of pregnancy complications. Compared to traditional 2D ultrasound (US…
FetalFlex: Anatomy-Guided Diffusion Model for Flexible Control on Fetal Ultrasound Image Synthesis
Yaofei Duan, Tao Tan, Zhiyuan Zhu +14
Fetal ultrasound (US) examinations require the acquisition of multiple planes, each providing unique diagnostic information to evaluate fetal development and screening for congenit…
Flip Learning: Weakly Supervised Erase to Segment Nodules in Breast Ultrasound
Yuhao Huang, Ao Chang, Haoran Dou +8
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, d…
Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation
Junxuan Yu, Rusi Chen, Yongsong Zhou +7
Echocardiography video is a primary modality for diagnosing heart diseases, but the limited data poses challenges for both clinical teaching and machine learning training. Recently…
Robust Box Prompt based SAM for Medical Image Segmentation
Yuhao Huang, Xin Yang, Han Zhou +4
The Segment Anything Model (SAM) can achieve satisfactory segmentation performance under high-quality box prompts. However, SAM's robustness is compromised by the decline in box qu…
Mitral Regurgitation Recognition based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification
Zhe Liu, Xiliang Zhu, Tong Han +7
Mitral regurgitation (MR) is a serious heart valve disease. Early and accurate diagnosis of MR via ultrasound video is critical for timely clinical decision-making and surgical int…
FetusMapV2: Enhanced Fetal Pose Estimation in 3D Ultrasound
Chaoyu Chen, Xin Yang, Yuhao Huang +11
Fetal pose estimation in 3D ultrasound (US) involves identifying a set of associated fetal anatomical landmarks. Its primary objective is to provide comprehensive information about…