使用LBP变异直方图的脑MR图像水平识别

Abraham Varghese, R. Varghese, K. Balakrishnan, J. S. Paul
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引用次数: 5

摘要

利用局部二值模式(LBP)直方图提取的特征提取含有相似解剖结构的轴向脑切片。将局部方差加入到LBP中,得到纹理模式及其强度的旋转不变描述,称为修正LBP (MOD-LBP)。在本文中,我们比较了基于直方图的LBP特征(HF/LBP)和基于直方图的MOD-LBP特征(HF/MOD-LBP)在检索相似的轴向脑图像方面的效果。我们证明用基于局部距离变换的相似度度量代替局部直方图进一步提高了基于MOD-LBP的图像检索的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Level identification of brain MR images using histogram of a LBP variant
Axial brain slices containing similar anatomical structures are retrieved using features derived from the histogram of Local binary pattern (LBP). A rotation invariant description of texture in terms of texture patterns and their strength is obtained with the incorporation of local variance to the LBP, called Modified LBP (MOD-LBP). In this paper, we compare Histogram based Features of LBP (HF/LBP), against Histogram based Features of MOD-LBP (HF/MOD-LBP) in retrieving similar axial brain images. We show that replacing local histogram with a local distance transform based similarity metric further improves the performance of MOD-LBP based image retrieval.
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