1 citations · 2 across the 8 of their papers we have counts for
8 papers
A Language-Signal-Vision Multimodal Framework for Multitask Cardiac Analysis
Yuting Zhang, Tiantian Geng, Luoying Hao +9
Contemporary cardiovascular management involves complex consideration and integration of multimodal cardiac datasets, where each modality provides distinct but complementary physio…
An Efficient Model-Driven Groupwise Approach for Atlas Construction
Ziwei Zou, Bei Zou, Xiaoyan Kui +6
Atlas construction is fundamental to medical image analysis, offering a standardized spatial reference for tasks such as population-level anatomical modeling. While data-driven reg…
CardAIc-Agents: A Multimodal Framework with Hierarchical Adaptation for Cardiac Care Support
Yuting Zhang, Karina V. Bunting, Asgher Champsi +8
Cardiovascular diseases (CVDs) remain the foremost cause of mortality worldwide, a burden worsened by a severe deficit of healthcare workers. Artificial intelligence (AI) agents ha…
SACB-Net: Spatial-awareness Convolutions for Medical Image Registration
Xinxing Cheng, Tianyang Zhang, Wenqi Lu +3
Deep learning-based image registration methods have shown state-of-the-art performance and rapid inference speeds. Despite these advances, many existing approaches fall short in ca…
WiNet: Wavelet-based Incremental Learning for Efficient Medical Image Registration
Xinxing Cheng, Xi Jia, Wenqi Lu +4
Deep image registration has demonstrated exceptional accuracy and fast inference. Recent advances have adopted either multiple cascades or pyramid architectures to estimate dense d…
Development of Automated Neural Network Prediction for Echocardiographic Left ventricular Ejection Fraction
Yuting Zhang, Boyang Liu, Karina V. Bunting +11
The echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification of patients with heart failure (HF). In order to q…
Decoder-Only Image Registration
Xi Jia, Wenqi Lu, Xinxing Cheng +1
In unsupervised medical image registration, the predominant approaches involve the utilization of a encoder-decoder network architecture, allowing for precise prediction of dense,…
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems
Jintao Song, Wenqi Lu, Yunwen Lei +3
The Alternating Direction Method of Multipliers (ADMM) has gained significant attention across a broad spectrum of machine learning applications. Incorporating the over-relaxation…