Meng Ye
Orcid: 0000-0003-2210-3396Affiliations:
- Rutgers University, Piscataway, NJ, USA
According to our database1,
Meng Ye
authored at least 10 papers
between 2020 and 2024.
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Bibliography
2024
Unsupervised Exemplar-Based Image-to-Image Translation and Cascaded Vision Transformers for Tagged and Untagged Cardiac Cine MRI Registration.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
2023
SequenceMorph: A Unified Unsupervised Learning Framework for Motion Tracking on Cardiac Image Sequences.
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023
Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2023
Neural Deformable Models for 3D Bi-Ventricular Heart Shape Reconstruction and Modeling from 2D Sparse Cardiac Magnetic Resonance Imaging.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
2022
DeepRecon: Joint 2D Cardiac Segmentation and 3D Volume Reconstruction via a Structure-Specific Generative Method.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
An Unsupervised 3D Recurrent Neural Network for Slice Misalignment Correction in Cardiac MR Imaging.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020