Iterative Methods for Fast Reconstruction of Undersampled Dynamic Contrast-Enhanced MRI Data

0490787 - ÚTIA 2019 RIV SG eng C - Konferenční příspěvek (zahraniční konf.)
Walner, Hynek - Bartoš, Michal - Mangová, M. - Keunen, O. - Bjerkvig, R. - Jiřík, Radovan - Šorel, Michal
Iterative Methods for Fast Reconstruction of Undersampled Dynamic Contrast-Enhanced MRI Data.
World Congress on Medical Physics and Biomedical Engineering 2018. Singapore: Springer, 2019 - (Lhotská, L.; Sukupová, L.; Lacković, I.; Ibbott, G.), s. 267-271, č. článku 48. IFMBE Proceedings, volume 68/1. ISBN 978-981-10-9034-9. ISSN 1680-0737.
[World Congress on Medical Physics and Biomedical Engineering 2018. Praha (CZ), 03.06.2018-08.06.2018]
Grant CEP: GA ČR(CZ) GA16-13830S
Institucionální podpora: RVO:67985556 ; RVO:68081731
Klíčová slova: DCE-MRI * Iterative reconstruction techniques * Compressed sensing
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8); Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) (UPT-D)
http://library.utia.cas.cz/separaty/2018/ZOI/walner-0490787.pdf

This paper introduces new variational formulation for reconstruction from subsampled dynamic contrast-enhanced DCE-MRI data, that combines a data-driven approach using estimated temporal basis and total variation regularization (PCA TV). We also experimentally compares the performance of such model with two other state-of-the-art formulations. One models the shape of perfusion curves in time as a sum of a curve belonging to a low-dimensional space and a function sparse in a suitable domain (L + S model). The other possibility is to regularize both spatial and time domains (ICTGV). We are dealing with the specific situation of the DCE-MRI acquisition with a 9.4T small animal scanner, working with noisier signals than human scanners and with a smaller number of coil elements that can be used for parallel acquisition and small voxels. Evaluation of the selected methods is done through subsampled reconstruction of radially-sampled DCE-MRI data. Our analysis shows that compressed sensed MRI in the form of regularization can be used to increase the temporal resolution of acquisition while keeping a sufficient signal-to-noise ratio.
Trvalý link: http://hdl.handle.net/11104/0289571