Acceleration of Perfusion MRI Using Locally Low-Rank Plus Sparse Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F15%3A00451441" target="_blank" >RIV/68081731:_____/15:00451441 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26220/15:PU115145
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-22482-4_60" target="_blank" >http://dx.doi.org/10.1007/978-3-319-22482-4_60</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-22482-4_60" target="_blank" >10.1007/978-3-319-22482-4_60</a>
Alternative languages
Result language
angličtina
Original language name
Acceleration of Perfusion MRI Using Locally Low-Rank Plus Sparse Model
Original language description
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 permeabilityrelated 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 undersampling. 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JA - Electronics and optoelectronics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Latent Variable Analysis and Signal Separation. 12th International Conference, LVA/ICA 2015. Proceedings
ISBN
978-3-319-22481-7
ISSN
0302-9743
e-ISSN
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Number of pages
8
Pages from-to
514-521
Publisher name
Springer
Place of publication
Zürich
Event location
Liberec
Event date
Aug 25, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000363785500060