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Prior image based temporally constrained reconstruction algorithm for magnetic resonance guided high intensity focused ultrasound.
Med. Phys. 42, 6804-6814 (2015)
Purpose: A prior image based temporally constrained reconstruction (PITCR) algorithm was developed for obtaining accurate temperature maps having better volume coverage, and spatial, and temporal resolution than other algorithms for highly undersampled data in magnetic resonance (MR) thermometry. Methods: The proposed PITCR approach is an algorithm that gives weight to the prior image and performs accurate reconstruction in a dynamic imaging environment. The PITCR method is compared with the temporally constrained reconstruction (TCR) algorithm using pork muscle data. Results: The PITCR method provides superior performance compared to the TCR approach with highly undersampled data. The proposed approach is computationally expensive compared to the TCR approach, but this could be overcome by the advantage of reconstructing with fewer measurements. In the case of reconstruction of temperature maps from 16% of fully sampled data, the PITCR approach was 1.57× slower compared to the TCR approach, while the root mean square error using PITCR is 0.784 compared to 2.815 with the TCR scheme. Conclusions: The PITCR approach is able to perform more accurate reconstructions of temperature maps compared to the TCR approach with highly undersampled data in MR guided high intensity focused ultrasound.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Times Cited
Scopus
Cited By
Cited By
Altmetric
2.635
1.629
1
1
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Dynamic Imaging ; Image Reconstruction ; Mr Thermometry ; Mrghifu ; Temperature Maps
Sprache
englisch
Veröffentlichungsjahr
2015
HGF-Berichtsjahr
2015
ISSN (print) / ISBN
0094-2405
e-ISSN
1522-8541
Zeitschrift
Medical Physics
Quellenangaben
Band: 42,
Heft: 12,
Seiten: 6804-6814
Verlag
American Institute of Physics (AIP)
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30205 - Bioengineering and Digital Health
Forschungsfeld(er)
Enabling and Novel Technologies
PSP-Element(e)
G-505500-001
PubMed ID
26632038
WOS ID
WOS:000368244100005
Scopus ID
84946944936
Erfassungsdatum
2015-11-24