Phillips W E, Brown H K, Bouza J, Figueroa R E
Medical College of Georgia, Department of Radiology, Augusta 30912-3900, USA.
Magn Reson Imaging. 1996;14(1):59-72. doi: 10.1016/0730-725x(95)02043-s.
The purpose of this article is to demonstrate the application of a PC-based multiparameter full color composite display technique of MR images of 14 selected patients with neuropathology while assessing the ability of this technique to display clinically important neuroanatomic and neuropathologic tissues. Using a PC with a 386 microprocessor and full color 24-bit graphics display capabilities, custom and commercially available image-processing softwares were applied to spatially aligned multiparameter proton density, T1-weighted (with and/or without gadolinium-DTPA) and T2-weighted MR image sets obtained from 14 patients with known neuropathology to generate intensity-based color composites. Quantitative color channel applications were used to assess the ability of this technique to differentiate anatomically and pathologically confirmed tissue types into unique color regions within the full color spectrum display in each patient case. Based on the results of pathologic correlation and quantitative color imaging analysis, the application of full color composite generation techniques to multiple MR images of selected neuropathology cases represents a viable technique for displaying diagnostically relevant tissue contrast information in one color image. With this technique, it is possible to generate composites that simultaneously display uniquely color-coded neuroanatomic and neuropathologic tissue information within the context of partially natural-appearing images.
本文的目的是展示一种基于个人计算机的多参数全彩复合显示技术在14例经神经病理学确诊患者的磁共振成像(MR)中的应用,同时评估该技术显示具有临床重要意义的神经解剖和神经病理组织的能力。使用一台具有386微处理器和全彩24位图形显示功能的个人计算机,将定制的和市售的图像处理软件应用于从14例已知神经病理学患者获得的空间对齐的多参数质子密度、T1加权(有和/或无钆-DTPA)和T2加权MR图像集,以生成基于强度的颜色合成图像。定量颜色通道应用用于评估该技术在每个患者病例的全彩光谱显示中,将经解剖学和病理学证实的组织类型区分为独特颜色区域的能力。基于病理相关性和定量颜色成像分析的结果,将全彩复合生成技术应用于选定神经病理学病例的多个MR图像,代表了一种在一幅彩色图像中显示诊断相关组织对比信息的可行技术。使用该技术,可以生成在部分呈现自然外观的图像背景下,同时显示独特颜色编码的神经解剖和神经病理组织信息的合成图像。