Levin D N, Pelizzari C A, Chen G T, Chen C T, Cooper M D
Department of Radiology, University of Chicago Hospitals, IL 60637.
Radiology. 1988 Dec;169(3):817-23. doi: 10.1148/radiology.169.3.3263666.
Magnetic resonance imaging, computed tomographic, and positron emission tomographic studies of the brain provide complementary information, and many patients undergo more than one of these studies during the course of their diagnostic workup and treatment. A new technique for quantitative geometric correlation of such studies makes it possible to create integrated multimodality images by mapping features from one image onto an image obtained with another modality. The coordinate transformation between any pair of images is found by a semiautomatic algorithm for matching models of the patient's external surface as depicted in the two data sets. The resultant hybrid images, which combine complementary features of different studies, are often more useful for diagnosis and treatment planning than are the original single-modality images. The algorithm can also be used for spatial registration of baseline studies with follow-up images created with the same modality, which allows tracking of a lesion to detect subtle interval changes in size and shape. This technique can be applied to images acquired in routine clinical practice, since it is completely retrospective and does not necessitate special positioning or landmarking of the patient.
脑部的磁共振成像、计算机断层扫描和正电子发射断层扫描研究提供了互补信息，许多患者在诊断检查和治疗过程中会接受不止一项此类检查。一种用于此类研究的定量几何相关性的新技术，通过将一个图像的特征映射到用另一种模式获得的图像上，从而创建集成多模态图像成为可能。任意一对图像之间的坐标变换是通过一种半自动算法找到的，该算法用于匹配两个数据集中描绘的患者外表面模型。由此产生的混合图像结合了不同研究的互补特征，通常比原始的单模态图像对诊断和治疗规划更有用。该算法还可用于将基线研究与用相同模式创建的后续图像进行空间配准，这有助于追踪病变以检测其大小和形状的细微间隔变化。由于该技术完全是回顾性的，不需要患者进行特殊定位或标记，因此可应用于常规临床实践中获取的图像。
