Wendt R E
Department of Radiology, Baylor College of Medicine, Houston, TX 77030.
J Digit Imaging. 1994 May;7(2):95-7. doi: 10.1007/BF03168430.
Two statistics of the magnetic resonance (MR) image, the median and the standard deviation of the values of the significant pixels, can be used along with the type of image to adjust the contrast and brightness of the image (ie, to "window" it) automatically and robustly. The essential parts of this approach to automatic windowing are (1) avoidance of irrelevant pixels, (2) identification of the type of MR image from information stored in the image header, and (3) use of algorithms for the maximum and minimum values that reflect the preference of the intended viewer using a specific monitor and ambient lighting conditions for the different types of images. An evaluation in thirteen clinical studies yielded 91.5% (2312/2526) images requiring no further adjustment and the remaining 8.5% (214/2526) being improved by further adjustment.
磁共振（MR）图像的两个统计量，即重要像素值的中位数和标准差，可与图像类型一起用于自动且稳健地调整图像的对比度和亮度（即对其进行“窗宽窗位调整”）。这种自动窗宽窗位调整方法的关键部分包括：（1）避免无关像素；（2）从图像头部存储的信息中识别MR图像的类型；（3）使用算法确定最大值和最小值，这些算法反映了目标观察者在特定显示器和环境光条件下对不同类型图像的偏好。在13项临床研究中的评估结果显示，91.5%（2312/2526）的图像无需进一步调整，其余8.5%（214/2526）的图像经进一步调整后得到改善。
