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WALNER, H. BARTOŠ, M. MANGOVÁ, M. KEUNEN, O. BJERKVIG, R. JIŘÍK, R. ŠOREL, M.
Original Title
Iterative Methods for Fast Reconstruction of Undersampled Dynamic Contrast-Enhanced MRI Data
Type
conference paper
Language
English
Original Abstract
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. DCE-MRI, iterative reconstruction techniques, compressed sensing.
Keywords
DCE-MRI; Iterative reconstruction techniques; Compressed sensing
Authors
WALNER, H.; BARTOŠ, M.; MANGOVÁ, M.; KEUNEN, O.; BJERKVIG, R.; JIŘÍK, R.; ŠOREL, M.
Released
2. 1. 2019
ISBN
978-981-10-9035-6
Book
World Congress on Medical Physics and Biomedical Engineering 2018
Pages from
267
Pages to
271
Pages count
5
URL
https://link.springer.com/chapter/10.1007/978-981-10-9035-6_48
BibTex
@inproceedings{BUT149006, author="Hynek {Walner} and Michal {Bartoš} and Marie {Mangová} and Olivier {Keunen} and Rolf {Bjerkvig} and Radovan {Jiřík} and Michal {Šorel}", title="Iterative Methods for Fast Reconstruction of Undersampled Dynamic Contrast-Enhanced MRI Data", booktitle="World Congress on Medical Physics and Biomedical Engineering 2018", year="2019", pages="267--271", doi="10.1007/978-981-10-9035-6\{_}48", isbn="978-981-10-9035-6", url="https://link.springer.com/chapter/10.1007/978-981-10-9035-6_48" }