0490787 20240103220201.120180627235959.9 85048274819 000450908300048 10.1007/978-981-10-9035-6_48 5 s. P cav_un_epca*0496757978-981-10-9034-91680-0737267-271SingaporeSpringer2019LhotskáL.SukupováL.LackovićI.IbbottG.S. DCE-MRI Iterative reconstruction techniques Compressed sensing cav_un_auth*0362064 Department of Image Processing Walner Hynek UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0312355 Department of Image Processing Bartoš Michal UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0355652 Mangová M. CZ cav_un_auth*0362066 Keunen O. NO cav_un_auth*0362067 Bjerkvig R. NO cav_un_auth*0277120 Jiřík Radovan UPT-D D3: Magnetická rezonance a Kryogenika D3: Magnetic Resonance and Cryogenics Magnetic Resonance and Cryogenics Ústav přístrojové techniky AV ČR, v. v. i. cav_un_auth*0108377 Šorel Michal UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2018/ZOI/walner-0490787.pdf cav_un_auth*0338628 GA16-13830S GA ČR CZ 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. cav_un_auth*0362068 World Congress on Medical Physics and Biomedical Engineering 2018 20180603 20180608 Praha CZ JD 10000 10200 10201 2019 7 UPT-D 10000 10200 10201 PR UPT-D JD RVO:67985556 RVO:68081731 http://hdl.handle.net/11104/0289571 S 48 1* Article Microbiology 0.143 Q4 2019 85048274819 SCOPUS PUBMED 000450908300048 WOS cav_un_epca*0496757 World Congress on Medical Physics and Biomedical Engineering 2018 978-981-10-9034-9 1680-0737 267 271 Singapore Springer 2019 IFMBE Proceedings volume 68/1 340 Lhotská L. 340 Sukupová L. 340 Lacković I. 340 Ibbott G.S.