ArticlePloS one2014
Comparison of total variation with a motion estimation based compressed sensing approach for self-gated cardiac cine MRI in small animal studies.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 19 citations in OpenAlex.
- Image-Derived Volumetry During Forced Expiration Using a 3D Fermat Looped, Orthogonally Encoded Trajectory.Magnetic resonance in medicine · 2026Article
- Magnetic Induction Tomography Spectroscopy for Structural and Functional Characterization in Metallic Materials.Materials (Basel, Switzerland) · 2020Article
- Sparsity adaptive reconstruction for highly accelerated cardiac MRI.Magnetic resonance in medicine · 2019Article
- Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation Regularization Algorithm.Sensors (Basel, Switzerland) · 2018Article
- Split Bregman multicoil accelerated reconstruction technique: A new framework for rapid reconstruction of cardiac perfusion MRI.Medical physics · 2016Article
- A Novel Prior- and Motion-Based Compressed Sensing Method for Small-Animal Respiratory Gated CT.PloS one · 2016Article
- Self-Gated Late Gadolinium Enhancement at 7T to Image Rats with Reperfused Acute Myocardial Infarction.Korean journal of radiologyArticle
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeCompressed sensing (CS) has been widely applied to prospective cardiac cine MRI. The aim of this work is to study the benefits obtained by including motion estimation in the CS framework for small-animal retrospective cardiac cine.
methodsWe propose a novel B-spline-based compressed sensing method (SPLICS) that includes motion estimation and generalizes previous spatiotemporal total variation (ST-TV) methods by taking into account motion between frames. In addition, we assess the effect of an optimum weighting between spatial and temporal sparsity to further improve results. Both methods were implemented using the efficient Split Bregman methodology and were evaluated on rat data comparing animals with myocardial infarction with controls for several acceleration factors.
resultsST-TV with optimum selection of the weighting sparsity parameter led to results similar to those of SPLICS; ST-TV with large relative temporal sparsity led to temporal blurring effects. However, SPLICS always properly corrected temporal blurring, independently of the weighting parameter. At acceleration factors of 15, SPLICS did not distort temporal intensity information but led to some artefacts and slight over-smoothing. At an acceleration factor of 7, images were reconstructed without significant loss of quality.
conclusionWe have validated SPLICS for retrospective cardiac cine in small animal, achieving high acceleration factors. In addition, we have shown that motion modelling may not be essential for retrospective cine and that similar results can be obtained by using ST-TV provided that an optimum selection of the spatiotemporal sparsity weighting parameter is performed.
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