34 citations · 72 across the 29 of their papers we have counts for
33 papers
SonoWorld: Towards Interactive Pose-Controllable Ultrasound World Models
Zefan Yang, Zheyuan Zhang, Boris Maihe +7
Robotic ultrasound can standardize image acquisition and reduce operator workload and variability, but policy learning remains limited by the lack of realistic, controllable simula…
Learning Where to Look: Anatomical Grounding and Guided Attention for Cardiac MRI Vision-Language Models
Bangwei Guo, Xiao Chen, Boris Mailhe +8
Cardiac magnetic resonance imaging (CMR) enables assessment of cardiac anatomy, ventricular function, and myocardial tissue characteristics. Clinicians interpret these images by id…
RAU: Reference-based Anatomical Understanding with Vision Language Models
Yiwei Li, Yikang Liu, Jiaqi Guo +7
Anatomical understanding, which is the ability to identify, localize, or segment anatomical structures, is critical in medical image analysis; however, its progress is constrained…
DiffDenoise: Self-Supervised Medical Image Denoising with Conditional Diffusion Models
Basar Demir, Yikang Liu, Xiao Chen +5
Many self-supervised denoising approaches have been proposed in recent years. However, these methods tend to overly smooth images, resulting in the loss of fine structures that are…
Leveraging Diffusion Model and Image Foundation Model for Improved Correspondence Matching in Coronary Angiography
Lin Zhao, Xin Yu, Yikang Liu +4
Accurate correspondence matching in coronary angiography images is crucial for reconstructing 3D coronary artery structures, which is essential for precise diagnosis and treatment…
Adapting Vision Foundation Models for Real-time Ultrasound Image Segmentation
Xiaoran Zhang, Eric Z. Chen, Lin Zhao +6
We propose a novel approach that adapts hierarchical vision foundation models for real-time ultrasound image segmentation. Existing ultrasound segmentation methods often struggle w…
Label-Efficient Data Augmentation with Video Diffusion Models for Guidewire Segmentation in Cardiac Fluoroscopy
Shaoyan Pan, Yikang Liu, Lin Zhao +4
The accurate segmentation of guidewires in interventional cardiac fluoroscopy videos is crucial for computer-aided navigation tasks. Although deep learning methods have demonstrate…
Auxiliary Input in Training: Incorporating Catheter Features into Deep Learning Models for ECG-Free Dynamic Coronary Roadmapping
Yikang Liu, Lin Zhao, Eric Z. Chen +3
Dynamic coronary roadmapping is a technology that overlays the vessel maps (the "roadmap") extracted from an offline image sequence of X-ray angiography onto a live stream of X-ray…
Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models
Lin Zhao, Xiao Chen, Eric Z. Chen +3
Medical image segmentation is crucial for clinical decision-making, but the scarcity of annotated data presents significant challenges. Few-shot segmentation (FSS) methods show pro…
Federated Data Model
Xiao Chen, Shunan Zhang, Eric Z. Chen +4
In artificial intelligence (AI), especially deep learning, data diversity and volume play a pivotal role in model development. However, training a robust deep learning model often…
Spatiotemporal Diffusion Model with Paired Sampling for Accelerated Cardiac Cine MRI
Shihan Qiu, Shaoyan Pan, Yikang Liu +7
Current deep learning reconstruction for accelerated cardiac cine MRI suffers from spatial and temporal blurring. We aim to improve image sharpness and motion delineation for cine…
Clinically Feasible Diffusion Reconstruction for Highly-Accelerated Cardiac Cine MRI
Shihan Qiu, Shaoyan Pan, Yikang Liu +7
The currently limited quality of accelerated cardiac cine reconstruction may potentially be improved by the emerging diffusion models, but the clinically unacceptable long processi…
Enhancing Cardiac MRI Segmentation via Classifier-Guided Two-Stage Network and All-Slice Information Fusion Transformer
Zihao Chen, Xiao Chen, Yikang Liu +3
Cardiac Magnetic Resonance imaging (CMR) is the gold standard for assessing cardiac function. Segmenting the left ventricle (LV), right ventricle (RV), and LV myocardium (MYO) in C…
An Unsupervised Framework for Joint MRI Super Resolution and Gibbs Artifact Removal
Yikang Liu, Eric Z. Chen, Xiao Chen +2
The k-space data generated from magnetic resonance imaging (MRI) is only a finite sampling of underlying signals. Therefore, MRI images often suffer from low spatial resolution and…
Holistic Multi-Slice Framework for Dynamic Simultaneous Multi-Slice MRI Reconstruction
Daniel H. Pak, Xiao Chen, Eric Z. Chen +3
Dynamic Magnetic Resonance Imaging (dMRI) is widely used to assess various cardiac conditions such as cardiac motion and blood flow. To accelerate MR acquisition, techniques such a…
Computationally Efficient 3D MRI Reconstruction with Adaptive MLP
Eric Z. Chen, Chi Zhang, Xiao Chen +3
Compared with 2D MRI, 3D MRI provides superior volumetric spatial resolution and signal-to-noise ratio. However, it is more challenging to reconstruct 3D MRI images. Current method…
JoJoNet: Joint-contrast and Joint-sampling-and-reconstruction Network for Multi-contrast MRI
Lin Zhao, Xiao Chen, Eric Z. Chen +4
Multi-contrast Magnetic Resonance Imaging (MRI) generates multiple medical images with rich and complementary information for routine clinical use; however, it suffers from a long…
Robust Landmark-based Stent Tracking in X-ray Fluoroscopy
Luojie Huang, Yikang Liu, Li Chen +3
In clinical procedures of angioplasty (i.e., open clogged coronary arteries), devices such as balloons and stents need to be placed and expanded in arteries under the guidance of X…
Deep Statistic Shape Model for Myocardium Segmentation
Xiaoling Hu, Xiao Chen, Yikang Liu +3
Accurate segmentation and motion estimation of myocardium have always been important in clinic field, which essentially contribute to the downstream diagnosis. However, existing me…
Flow-based Visual Quality Enhancer for Super-resolution Magnetic Resonance Spectroscopic Imaging
Siyuan Dong, Gilbert Hangel, Eric Z. Chen +7
Magnetic Resonance Spectroscopic Imaging (MRSI) is an essential tool for quantifying metabolites in the body, but the low spatial resolution limits its clinical applications. Deep…
Invertible Sharpening Network for MRI Reconstruction Enhancement
Siyuan Dong, Eric Z. Chen, Lin Zhao +4
High-quality MRI reconstruction plays a critical role in clinical applications. Deep learning-based methods have achieved promising results on MRI reconstruction. However, most sta…
Multi-scale Neural ODEs for 3D Medical Image Registration
Junshen Xu, Eric Z. Chen, Xiao Chen +2
Image registration plays an important role in medical image analysis. Conventional optimization based methods provide an accurate estimation due to the iterative process at the cos…
Accelerating 3D MULTIPLEX MRI Reconstruction with Deep Learning
Eric Z. Chen, Yongquan Ye, Xiao Chen +6
Multi-contrast MRI images provide complementary contrast information about the characteristics of anatomical structures and are commonly used in clinical practice. Recently, a mult…
Cardiac Functional Analysis with Cine MRI via Deep Learning Reconstruction
Eric Z. Chen, Xiao Chen, Jingyuan Lyu +7
Retrospectively gated cine (retro-cine) MRI is the clinical standard for cardiac functional analysis. Deep learning (DL) based methods have been proposed for the reconstruction of…