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Abstract #2625

Application of Compressed Sensing to Minimize Pulsation Artifacts and Distortions in High Resolution Time-Of-Flight Imaging at 7 Tesla MRI

Anders Garpebring1, Maarten J. Versluis2, 3, Matthias J.P. van Osch2, 3

1Radiation Sciences, Ume University, Ume, Sweden, Sweden; 2Radiology, Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands; 3CJ Gorter Center for high field MRI, Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands

Ultra high field MRI time-of-flight angiograms can often be seriously degraded by pulsation artifacts. A method based on random order sampling, retrospective gating and L1-SPIRiT reconstruction was developed and tested on a 7 T scanner. The results confirmed that the proposed method can reduce the flow artifacts.

Keywords

accelerate acquiring acquisition advanced anders aneurysms angiography application applied appreciated arising around arteries artifact artifacts audience auto blur brain calibration cardiac central channel channels clear coil collected combination combinations combined compressed compressing compression contained cost cycle cyclic deducted degraded denser detection differentiation distortion distortions enabling entire especially evidence expected expense feasible field final finally flight flow footprint free frequencies frequency frequently fully furthermore future gating gradient head human hypothesize improvements induced instance intervals introduced isolate iterations kernel likely longer many matrix medical memory might minimize minimized needed ordinary original part partial processes proposed pulsation pulsations pulse radiation radiology random reconstructed reconstruction recorded reduce reduced reduction regularization relatively remain remaining reordering researchers resolution retrospective reuse sampled sampling scanner scheme sciences sense sensing separate settings sharper smallest solution space spaces spatial spirit started stripe stroke subsequently substantially subtle suited synchronously taking target timing transform tree twofold ultra unit vascular vessels visualization wave wavelets