ArticleComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society2024
Motion correction and super-resolution for multi-slice cardiac magnetic resonance imaging via an end-to-end deep learning approach.
Article in Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- Deep learning approach to super-resolution correction of brain MRI motion artifacts for accurate hippocampal volumetry.Scientific reports · 2026Article
- Cross-Modality Whole-Heart MRI Reconstruction with Deep Motion Correction and Super-Resolution.Sensors (Basel, Switzerland) · 2026Article
- Systematic Review and Meta-analysis of AI-driven MRI Motion Artifact Detection and Correction.ArXiv · 2025Article
- Cine cardiac magnetic resonance segmentation using temporal-spatial adaptation of prompt-enabled segment-anything-model: a feasibility study.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025Article
- Hypertrophic obstructive cardiomyopathy-left ventricular outflow tract shapes and their hemodynamic influences applying CMR.The international journal of cardiovascular imaging · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Accurate reconstruction of a high-resolution 3D volume of the heart is critical for comprehensive cardiac assessments. However, cardiac magnetic resonance (CMR) data is usually acquired as a stack of 2D short-axis (SAX) slices, which suffers from the inter-slice misalignment due to cardiac motion and data sparsity from large gaps between SAX slices. Therefore, we aim to propose an end-to-end deep learning (DL) model to address these two challenges simultaneously, employing specific model components for each challenge. The objective is to reconstruct a high-resolution 3D volume of the heart (V
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.