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Reduced Data Acquisition Methods in Cardiac Imaging
Author(s) -
Sebastian Kozerke,
Jeffrey Tsao
Publication year - 2004
Publication title -
topics in magnetic resonance imaging
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 53
eISSN - 1536-1004
pISSN - 0899-3459
DOI - 10.1097/01.rmr.0000132789.84706.9d
Subject(s) - data acquisition , computer science , acceleration , cardiac imaging , set (abstract data type) , focus (optics) , artificial intelligence , computer vision , process (computing) , medicine , physics , radiology , classical mechanics , optics , programming language , operating system
In cardiac imaging, acquisition speed is of primary importance. While improved performance has mainly been achieved through improvements in gradient hardware in the past, further developments along this direction are limited due to physiological constraints such as the risk of peripheral nerve stimulation. With the introduction of parallel imaging, alternative means for increasing acquisition speed have become available. Using information from multiple receiver coils, images can be reconstructed from a sparsely sampled set of data. In practice, parallel imaging allows for 2- to 3-fold acceleration of the imaging process in typical cardiac applications. Further increases in acquisition speed are, however, difficult to achieve for current clinical field strengths and typical field of views. To address the limited gain in acquisition speed achievable with parallel imaging, a new set of methods has been proposed to take into account the similarity of image information at different time points during a dynamic series. Using these methods, 5- to 8-fold acceleration can be achieved in cardiac imaging. It is the purpose of this paper to review cardiac applications of reduced data acquisition methods with focus on parallel imaging and the recently developed k-t BLAST and k-t SENSE techniques.

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