Zhuge Ying, Udupa Jayaram K, Liu Jiamin, Saha Punam K
Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA.
Comput Med Imaging Graph. 2009 Jan;33(1):7-16. doi: 10.1016/j.compmedimag.2008.09.004. Epub 2008 Nov 11.
An automatic, simple, and image intensity standardization-based strategy for correcting background inhomogeneity in MR images is presented in this paper. Image intensities are first transformed to a standard intensity gray scale by a standardization process. Different tissue sample regions are then obtained from the standardized image by simply thresholding based on fixed intensity intervals. For each tissue region, a polynomial is fitted to the estimated discrete background intensity variation. Finally, a combined polynomial is determined and used for correcting the intensity inhomogeneity in the whole image. The above procedure is repeated on the corrected image iteratively until the size of the extracted tissue regions does not change significantly in two successive iterations. Intensity scale standardization is effected to make sure that the corrected image is not biased by the fitting strategy. The method has been tested on a number of simulated and clinical MR images. These tests and a comparison with the method of non-parametric non-uniform intensity normalization (N3) indicate that the method is effective in background intensity inhomogeneity correction and may have a slight edge over the N3 method.
本文提出了一种基于自动、简单且基于图像强度标准化的策略，用于校正磁共振成像（MR）中的背景不均匀性。首先通过标准化过程将图像强度转换为标准强度灰度级。然后基于固定强度区间进行简单阈值处理，从标准化图像中获取不同的组织样本区域。对于每个组织区域，拟合一个多项式以估计离散背景强度变化。最后，确定一个组合多项式并用于校正整个图像中的强度不均匀性。在校正后的图像上迭代重复上述过程，直到在连续两次迭代中提取的组织区域大小没有显著变化。进行强度尺度标准化以确保校正后的图像不受拟合策略的影响。该方法已在多个模拟和临床MR图像上进行了测试。这些测试以及与非参数非均匀强度归一化（N3）方法的比较表明，该方法在背景强度不均匀性校正方面是有效的，并且可能比N3方法略有优势。
