Vannier M W, Butterfield R L, Jordan D, Murphy W A, Levitt R G, Gado M
Radiology. 1985 Jan;154(1):221-4. doi: 10.1148/radiology.154.1.3964938.
Magnetic resonance (MR) imaging systems produce spatial distribution estimates of proton density, relaxation time, and flow, in a two dimensional matrix form that is analogous to that of the image data obtained from multispectral imaging satellites. Advanced NASA satellite image processing offers sophisticated multispectral analysis of MR images. Spin echo and inversion recovery pulse sequence images were entered in a digital format compatible with satellite images and accurately registered pixel by pixel. Signatures of each tissue class were automatically determined using both supervised and unsupervised classification. Overall tissue classification was obtained in the form of a theme map. In MR images of the brain, for example, the classes included CSF, gray matter, white matter, subcutaneous fat, muscle, and bone. These methods provide an efficient means of identifying subtle relationships in a multi-image MR study.
磁共振（MR）成像系统以二维矩阵形式生成质子密度、弛豫时间和血流的空间分布估计值，这种形式类似于从多光谱成像卫星获得的图像数据。美国国家航空航天局（NASA）先进的卫星图像处理技术为MR图像提供了复杂的多光谱分析。自旋回波和反转恢复脉冲序列图像以与卫星图像兼容的数字格式输入，并逐像素精确配准。使用监督分类和非监督分类自动确定每个组织类别的特征。以专题地图的形式获得整体组织分类。例如，在脑部的MR图像中，类别包括脑脊液、灰质、白质、皮下脂肪、肌肉和骨骼。这些方法为在多图像MR研究中识别细微关系提供了一种有效的手段。
