Wanschura T, Coley D A, Vennart W, Gandy S
Department of Physics, University of Exeter, UK.
Magn Reson Imaging. 1999 Feb;17(2):313-7. doi: 10.1016/s0730-725x(98)00169-6.
A simple yet highly efficient artificial intelligence technique utilizing a genetic algorithm is used to register time-separated pairs of MRI data sets. To encourage others to try the approach, the algorithm is presented by way of a simple example to a 2-D data set; it is equally applicable to 3-D data. The technique is reliably found to reduce mismatch in images of the distal-interphalangeal joint from the order of several mm to just 200 microm (one pixel). The method and transformation are general and would be suitable for locating physical changes between any image data sets. We believe the technique to be of use in functional imaging, measurement of disease progression with time (e.g., degradation of cartilage in arthritic disease) and pre/post-surgical studies.
一种利用遗传算法的简单却高效的人工智能技术被用于对时间上分离的成对MRI数据集进行配准。为鼓励他人尝试该方法,通过一个二维数据集的简单示例来展示该算法;它同样适用于三维数据。可靠地发现,该技术可将远侧指间关节图像中的失配从几毫米量级降低至仅200微米(一个像素)。该方法及变换具有通用性,适用于定位任何图像数据集之间的物理变化。我们认为该技术可用于功能成像、疾病随时间进展的测量(例如,关节炎疾病中软骨的退化)以及手术前后研究。