Lianming Wu
Orcid: 0000-0001-7381-5436
According to our database1,
Lianming Wu
authored at least 15 papers
between 2014 and 2025.
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Bibliography
2025
CTSL: Codebook-based Temporal-Spatial Learning for Accurate Non-Contrast Cardiac Risk Prediction Using Cine MRIs.
CoRR, July, 2025
U2AD: Uncertainty-based Unsupervised Anomaly Detection Framework for Detecting T2 Hyperintensity in MRI Spinal Cord.
CoRR, March, 2025
Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis.
CoRR, March, 2025
The state-of-the-art in cardiac MRI reconstruction: Results of the CMRxRecon challenge in MICCAI 2023.
Medical Image Anal., 2025
Dynamic mask stitching-guided region consistency for semi-supervised 3D medical image segmentation.
Expert Syst. Appl., 2025
A multimodal deep learning framework for automated major adverse cardiovascular events prediction in patients with end-stage renal disease integrating clinical and cardiac MRI data.
Displays, 2025
2024
Toward Accurate Cardiac MRI Segmentation With Variational Autoencoder-Based Unsupervised Domain Adaptation.
IEEE Trans. Medical Imaging, August, 2024
Boosting knowledge diversity, accuracy, and stability via tri-enhanced distillation for domain continual medical image segmentation.
Medical Image Anal., 2024
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI.
CoRR, 2024
Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy.
CoRR, 2024
Analysis of the Discriminability of Three Types of CMR Image Features for Cardiomyopathy.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
2023
Segmentation of Pericardial Adipose Tissue in CMR Images: A Benchmark Dataset MRPEAT and a Triple-Stage Network 3SUnet.
IEEE Trans. Medical Imaging, 2023
2017
Myocardium Segmentation From DE MRI Using Multicomponent Gaussian Mixture Model and Coupled Level Set.
IEEE Trans. Biomed. Eng., 2017
2014
Myocardium segmentation combining T2 and DE MRI using Multi-Component Bivariate Gaussian mixture model.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014