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2015 ; 41
(3
): 573-85
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Image reconstruction: an overview for clinicians
#MMPMID24962650
Hansen MS
; Kellman P
J Magn Reson Imaging
2015[Mar]; 41
(3
): 573-85
PMID24962650
show ga
Image reconstruction plays a critical role in the clinical use of magnetic
resonance imaging (MRI). The MRI raw data is not acquired in image space and the
role of the image reconstruction process is to transform the acquired raw data
into images that can be interpreted clinically. This process involves multiple
signal processing steps that each have an impact on the image quality. This
review explains the basic terminology used for describing and quantifying image
quality in terms of signal-to-noise ratio and point spread function. In this
context, several commonly used image reconstruction components are discussed. The
image reconstruction components covered include noise prewhitening for phased
array data acquisition, interpolation needed to reconstruct square pixels, raw
data filtering for reducing Gibbs ringing artifacts, Fourier transforms
connecting the raw data with image space, and phased array coil combination. The
treatment of phased array coils includes a general explanation of parallel
imaging as a coil combination technique. The review is aimed at readers with no
signal processing experience and should enable them to understand what role basic
image reconstruction steps play in the formation of clinical images and how the
resulting image quality is described.