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首页> 外文期刊>Magnetic resonance in medicine: official journal of the Society of Magnetic Resonance in Medicine >Combination of signals from array coils using image-based estimation of coil sensitivity profiles.
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Combination of signals from array coils using image-based estimation of coil sensitivity profiles.

机译:使用基于图像的线圈灵敏度分布图估计,组合来自阵列线圈的信号。

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摘要

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.
机译:众所周知,组合来自阵列线圈的图像数据的最佳无偏方法是线圈信号的逐像素总和,每个信号均由像素位置处的各个线圈灵敏度加权。一种实用的选择是将来自线圈的图像组合为平方和(SOS)的平方根,这可以降低信噪比(SNR)并引入偏差。这项工作描述了如何用图像衍生的量代替线圈灵敏度,从而使接近最佳的信号组合达到全局强度缩放。典型的缩放是通过单个线圈灵敏度或阵列中某些或所有线圈的灵敏度的线性或SOS组合。当线圈具有不相等的噪声水平时,该方法可降低信号偏置,提高SNR,并可以减少图像伪影。它可以产生相位校正的数据,从而完全消除偏差。另外,该方法允许将来自包括高度局限性线圈(例如前列腺线圈和外部骨盆阵列)的阵列中的图像与接近最佳的SNR和强度调制相结合,从而使它们更易于查看。

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