activity
20202024
most citedMulti-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis

5 citations · 13 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation

Bangwei Guo, Meng Ye, Yunhe Gao +3

Despite the advances in learning-based image segmentation approach, the accurate segmentation of cardiac structures from magnetic resonance imaging (MRI) remains a critical challen…

eess.IV2024

Learning Volumetric Neural Deformable Models to Recover 3D Regional Heart Wall Motion from Multi-Planar Tagged MRI

Meng Ye, Bingyu Xin, Bangwei Guo +2

Multi-planar tagged MRI is the gold standard for regional heart wall motion evaluation. However, accurate recovery of the 3D true heart wall motion from a set of 2D apparent motion…

cs.CV2024

Continuous Spatio-Temporal Memory Networks for 4D Cardiac Cine MRI Segmentation

Meng Ye, Bingyu Xin, Leon Axel +1

Current cardiac cine magnetic resonance image (cMR) studies focus on the end diastole (ED) and end systole (ES) phases, while ignoring the abundant temporal information in the whol…

eess.IV2024★ 2 cited

The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023

Jun Lyu, Chen Qin, Shuo Wang +47

Cardiac MRI, crucial for evaluating heart structure and function, faces limitations like slow imaging and motion artifacts. Undersampling reconstruction, especially data-driven alg…

eess.IV2023★ 2 cited

Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction

Bingyu Xin, Meng Ye, Leon Axel +1

The key to dynamic or multi-contrast magnetic resonance imaging (MRI) reconstruction lies in exploring inter-frame or inter-contrast information. Currently, the unrolled model, an…

eess.IV2021★ 4 cited

Learned Half-Quadratic Splitting Network for MR Image Reconstruction

Bingyu Xin, Timothy S. Phan, Leon Axel +1

Magnetic Resonance (MR) image reconstruction from highly undersampled -space data is critical in accelerated MR imaging (MRI) techniques. In recent years, deep learning-based me…

cs.CV2020★ 5 cited

Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis

Bingyu Xin, Yifan Hu, Yefeng Zheng +1

Magnetic Resonance (MR) images of different modalities can provide complementary information for clinical diagnosis, but whole modalities are often costly to access. Most existing…