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Detail publikace
DAŇKOVÁ, M. RAJMIC, P. JIŘÍK, R.
Originální název
Acceleration of Perfusion MRI Using Locally Low-Rank Plus Sparse Model
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Perfusion magnetic resonance imaging is a technique used in diagnostics and evaluation of therapy response, where the quantification is done by analyzing the perfusion curves. Perfusion- and permeability-related tissue parameters can be obtained using advanced pharmacokinetic models, but, these models require high spatial and temporal resolution of the acquisition simultaneously. The resolution is usually increased by means of compressed sensing: the acquisition is accelerated by under-sampling. However, these techniques need to be improved to achieve higher spatial resolution and/or to allow multislice acquisition. We propose a modification of the L+S model for the reconstruction of perfusion curves from the under-sampled data. This model assumes that perfusion data can be modelled as a superposition of locally low-rank data and data that are sparse in the spectral domain. We show that our model leads to a better performance compared to the other methods.
Klíčová slova
Perfusion; MRI; DCE-MRI; Compressed sensing; Sparsity; Locally low-rank
Autoři
DAŇKOVÁ, M.; RAJMIC, P.; JIŘÍK, R.
Rok RIV
2015
Vydáno
25. 8. 2015
Nakladatel
Springer
Místo
Liberec
ISBN
978-3-319-22481-7
Kniha
Latent Variable Analysis and Signal Separation
Strany od
514
Strany do
521
Strany počet
8
BibTex
@inproceedings{BUT115848, author="Marie {Mangová} and Pavel {Rajmic} and Radovan {Jiřík}", title="Acceleration of Perfusion MRI Using Locally Low-Rank Plus Sparse Model", booktitle="Latent Variable Analysis and Signal Separation", year="2015", pages="514--521", publisher="Springer", address="Liberec", doi="10.1007/978-3-319-22482-4\{_}60", isbn="978-3-319-22481-7" }