Patriarche Julia, Erickson Bradley
Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester, MN 55905, USA.
J Digit Imaging. 2004 Sep;17(3):158-74. doi: 10.1007/s10278-004-1010-x. Epub 2004 Jun 29.
Serial imaging is frequently performed on patients with diseases of the brain, to track and observe changes. Magnetic resonance imaging provides very detailed and rich information, and is therefore used frequently for this application. The data provided by MR can be so plentiful; however, that it obfuscates the information the radiologist seeks. A system which could reduce the large quantity of primitive data to a smaller and more informative subset of data, emphasizing change, would be useful. This article discusses motivating factors for the production of an automated process to this effect, and reviews the approaches of previous authors. The discussion is focused on brain tumors and multiple sclerosis, but many of the ideas are applicable to other disease processes, as well.
对于患有脑部疾病的患者，经常会进行系列成像以跟踪和观察变化。磁共振成像能提供非常详细和丰富的信息，因此常用于此目的。然而，磁共振提供的数据可能非常多，以至于会模糊放射科医生所寻找的信息。一个能够将大量原始数据减少到更小且更具信息量的数据子集，并突出变化的系统将很有用。本文讨论了促成产生这种自动化流程的因素，并回顾了先前作者的方法。讨论聚焦于脑肿瘤和多发性硬化症，但许多观点也适用于其他疾病过程。
