苏木精-伊红染色组织图像的无监督归一化方法。
Unsupervised method for normalization of hematoxylin-eosin stain in histological images.
机构信息
Center of Mathematics, Computing and Cognition, Federal University of ABC, Av. dos Estados, 5001, 09210-580 Santo André, São Paulo, Brazil.
Department of Histology and Morphology, Institute of Biomedical Science, Federal University of Uberlândia, Av. Amazonas, S/N, 38405-320 Uberlândia, Minas Gerais, Brazil.
出版信息
Comput Med Imaging Graph. 2019 Oct;77:101646. doi: 10.1016/j.compmedimag.2019.101646. Epub 2019 Aug 14.
Histological images stained with hematoxylin-eosin are widely used by pathologists for cancer diagnosis. However, these images can have color variations that highly influence the histological image processing techniques. To deal with this potential limitation, normalization methods are useful for color correction. In this paper, a histological image color normalization is presented by considering the biological and hematoxylin-eosin properties. To this end, the stain representation of a reference image was applied in place of the original images representation, allowing the preservation of histological structures. This proposal was evaluated on histological images with great variations of contrast, and both visual and quantitative analyzes yielded promising results.
苏木精-伊红染色的组织学图像被病理学家广泛用于癌症诊断。然而，这些图像可能存在颜色变化，这会极大地影响组织学图像处理技术。为了解决这个潜在的局限性，归一化方法对于颜色校正很有用。在本文中，通过考虑生物和苏木精-伊红特性，提出了一种组织学图像的颜色归一化方法。为此，将参考图像的染色表示应用于原始图像的表示，从而保留组织结构。该方法在对比度变化较大的组织学图像上进行了评估，并且视觉和定量分析都取得了有希望的结果。
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