10 papers
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…
Fairness-Aware Multi-view Evidential Learning with Adaptive Prior
Haishun Chen, Cai Xu, Jinlong Yu +5
Multi-view evidential learning aims to integrate information from multiple views to improve prediction performance and provide trustworthy uncertainty esitimation. Most previous me…
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…
TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker
Qi Li, Shaheer U. Saeed, Yuliang Huang +24
Trackerless freehand ultrasound reconstruction aims to reconstruct 3D volumes from sequences of 2D ultrasound images without relying on external tracking systems. By eliminating th…