Combination of signals from array coils using image-based estimation of coil sensitivity profiles.

Abstract

It is well established that the optimal unbiased way to combine image data from array coils is a pixel-by-pixel sum of coil signals, with each signal weighted by the individual coil sensitivity at the location of the pixel. A pragmatic alternative combines the images from the coils as the square root of the sum of squares (SOS), which can reduce the signal-to-noise ratio (SNR) and introduce bias. This work describes how to replace coil sensitivity by an image-derived quantity that enables close to optimal signal combination up to a global intensity scaling. Typical scaling is by an individual coil sensitivity or a linear or SOS combination of the sensitivities of some or all of the coils in the array. The method decreases signal bias, improves SNR when coils have unequal noise levels, and can reduce image artifacts. It can produce phase-corrected data, which eliminates bias completely. In addition, the method allows images from arrays that include highly localized coils, such as a prostate coil and external pelvic array, to be combined with near-optimal SNR and an intensity modulation that makes them easier to view.