MULTISPECTRAL ANALYSIS OF MAGNETIC-RESONANCE IMAGES
MULTISPECTRAL ANALYSIS OF MAGNETIC-RESONANCE IMAGES
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DOI：
10.1148/radiology.154.1.3964938
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发表时间：
1985-01-01
期刊：
影响因子：
19.7
通讯作者：
GADO, M
中科院分区：
文献类型：
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作者：
VANNIER, MW;BUTTERFIELD, RL;GADO, M
磁共振（MR）成像系统以二维矩阵形式产生质子密度、弛豫时间和流的空间分布估计，该二维矩阵形式类似于从多谱成像卫星获得的图像数据的二维矩阵形式。先进的NASA卫星图像处理提供了复杂的MR图像多光谱分析。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。使用监督和非监督分类自动确定每个组织类别的特征。以主题图的形式获得总体组织分类。例如，在大脑的MR图像中，类别包括CSF、灰质、白色物质、皮下脂肪、肌肉和骨骼。这些方法提供了在多图像MR研究中识别微妙关系的有效手段。
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.