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Image Background Inhomogeneity Correction in MRI via Intensity Standardization

机译:通过强度标准化校正MRI中的图像背景不均匀性

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摘要

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.
机译:本文提出了一种基于自动,简单且基于图像强度标准化的校正MR图像背景不均匀性的策略。首先通过标准化过程将图像强度转换为标准强度灰度。然后,通过基于固定强度间隔的简单阈值处理,从标准化图像中获得不同的组织样本区域。对于每个组织区域,将多项式拟合到估计的离散背景强度变化。最后,确定组合多项式并将其用于校正整个图像中的强度不均匀性。在校正的图像上反复重复上述过程,直到两次连续迭代中提取的组织区域的大小没有明显变化为止。进行强度标尺标准化,以确保校正后的图像不会因拟合策略而产生偏差。该方法已经在许多模拟和临床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,该方法在背景强度非均匀性校正方面有效,并且可能比N3方法略有优势。

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