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</script>doi: 10.1002/mrm.21943
pmid: 19319899
AbstractTraditional methods for magnetic resonance angiography (MRA) involve the radiofrequency excitation of vascular spins within a selected region of tissue, followed by gradient localization and imaging of those spins within that same region. Signals that unfaithfully localize within the imaging volume, so‐called “ghost artifacts”, have historically been considered undesirable since they degrade image quality and every effort is made to suppress them. To the contrary, we hypothesized that these ghost artifacts could be manipulated to create detailed angiograms of the human body. In this initial demonstration of the method, which we call “Ghost MRA,” we show that the human arterial system can be depicted with exquisite anatomic detail and near total suppression of background signal. Moreover, unlike alternative unenhanced methods, Ghost MRA can be acquired without the need for cardiac synchronization. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
Adult, Male, Image Interpretation, Computer-Assisted, Humans, Reproducibility of Results, Female, Image Enhancement, Sensitivity and Specificity, Algorithms, Magnetic Resonance Angiography
Adult, Male, Image Interpretation, Computer-Assisted, Humans, Reproducibility of Results, Female, Image Enhancement, Sensitivity and Specificity, Algorithms, Magnetic Resonance Angiography
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
