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中文摘要：
脑白质病变诊断是医学研究和病理分析的重要方面。颅脑核磁共振图像的白质分割在诊断中起着非常重要的作用，其分割的准确性直接影响后续的分析和诊断研究。本文提出了一种基于局部Walsh变换和非负矩阵分解的大脑核磁共振图像白质分割算法。算法首先对颅脑图像进行局部Walsh变换，选择鉴别性能好的特征得到特征矩阵，然后对其进行非负矩阵分解并得到白质的分割结果。实验表明，本方法计算简单，精度比较高，可以得到比较理想的分割结果。
英文摘要：
The diagnosis of brain white matter lesions is an important aspect of medical research. White matter segmentation of brain MR image plays a key role in diagnosis, and the accuracy of segmentation directly influences the following analysis and diagnostic processing. This paper proposes an algorithm for white matter segmentation of brain MR images based on local Walsh transform and non-negative matrix factorization. The algorithm first operates a local Walsh transform on the pixels of a brain image, and then selects the features with good discrimination to get the feature matrix,and finally gets the results of segmentation by no,negative matrix factorization on the feature matrix. The experiments show that the proposed method is simple with high precision, and can gain reasonable results.
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