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Found 7 papers, 3 papers with code
MorphiNet: A Graph Subdivision Network for Adaptive Bi-ventricle Surface Reconstruction
This approach represents a significant advancement in addressing the challenges of CMR-based heart model reconstruction, potentially improving digital twin computational analyses of cardiac structure and functions.
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI
To the best of our knowledge, the CMRxRecon2024 dataset is the largest and most diverse publicly available cardiac k-space dataset.
Goal-conditioned reinforcement learning for ultrasound navigation guidance
Transesophageal echocardiography (TEE) plays a pivotal role in cardiology for diagnostic and interventional procedures.
Cardiac ultrasound simulation for autonomous ultrasound navigation
However, the image quality varies with operator skills as acquiring and interpreting ultrasound images requires extensive training due to the imaging artefacts, the range of acquisition parameters and the variability of patient anatomies.
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images
Our dataset contains short axis images from 4 different MR scanners and 3 different pathology groups.
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data
The framework consists of a deep learning model for the reconstruction of 2D+t cardiac cine MRI images from undersampled data, an image quality-control step to detect good quality reconstructions, followed by a deep learning model for bi-ventricular segmentation, a quality-control step to detect good quality segmentations and automated calculation of cardiac functional parameters.
4DFlowNet: Super-Resolution 4D Flow MRI using Deep Learning and Computational Fluid Dynamics
4D-flow magnetic resonance imaging (MRI) is an emerging imaging technique where spatiotemporal 3D blood velocity can be captured with full volumetric coverage in a single non-invasive examination.
