Yokoo Takeshi, Bae Won C, Hamilton Gavin, Karimi Afshin, Borgstede James P, Bowen Brian C, Sirlin Claude B, Chung Christine B, Crues John V, Bradley William G, Bydder Graeme M
Department of Radiology, University of California, San Diego, San Diego, CA 92103-8226, USA.
J Comput Assist Tomogr. 2010 May-Jun;34(3):317-31. doi: 10.1097/RCT.0b013e3181d3449a.
Weighting is the term most frequently used to describe magnetic resonance pulse sequences and the concept most commonly used to relate image contrast to differences in magnetic resonance tissue properties. It is generally used in a qualitative sense with the single tissue property thought to be most responsible for the contrast used to describe the weighting of the image as a whole. This article describes a quantitative approach for understanding the weighting of sequences and images, using filters and partial derivatives of signal with respect to logarithms of tissue property values. Univariate and multivariate models are described for several pulse sequences including methods for maximizing weighting and calculating both sequence and image weighting ratios. The approach provides insights into difficulties associated with qualitative use of the concept of weighting and a quantitative basis for assessing the signal, contrast, and weighting of commonly used sequences and images.
加权是描述磁共振脉冲序列最常用的术语，也是将图像对比度与磁共振组织特性差异相关联的最常用概念。它通常在定性意义上使用，单一组织特性被认为是造成用于描述整个图像加权的对比度的主要原因。本文描述了一种定量方法，用于理解序列和图像的加权，使用滤波器以及信号相对于组织特性值对数的偏导数。针对几种脉冲序列描述了单变量和多变量模型，包括最大化加权以及计算序列和图像加权比的方法。该方法深入探讨了与加权概念定性使用相关的困难，并为评估常用序列和图像的信号、对比度和加权提供了定量基础。
