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Offset-sparsity decomposition for automated enhancement of color microscopic image of stained specimen in histopathology

机译:偏移稀疏分解,用于自动增强组织病理学中染色标本的彩色显微图像

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摘要

We propose an offset-sparsity decomposition (OSD) method for the enhancement of a color microscopic image of a stained specimen. The method decomposes vectorized spectral images into offset terms and sparse terms. A sparse term represents an enhanced image, and an offset term represents a “shadow.” The related optimization problem is solved by computational improvement of the accelerated proximal gradient method used initially to solve the related rank-sparsity decomposition problem. Removal of an image-adapted color offset yields an enhanced image with improved colorimetric differences among the histological structures. This is verified by a no-reference colorfulness measure estimated from 35 specimens of the human liver and 1 specimen of the mouse liver stained with hematoxylin and eosin, 6 specimens of the mouse liver stained with Sudan III, and 3 specimens of the human liver stained with the anti-CD34 monoclonal antibody. The colorimetric difference improves on average by 43.86% with a 99% confidence interval (CI) of [35.35%, 51.62%]. Furthermore, according to the mean opinion score, estimated on the basis of the evaluations of five pathologists, images enhanced by the proposed method exhibit an average quality improvement of 16.60% with a 99% CI of [10.46%, 22.73%].
机译:我们提出了一种偏移稀疏分解(OSD)方法,用于增强染色样本的彩色显微图像。该方法将矢量化频谱图像分解为偏移项和稀疏项。稀疏项表示增强的图像,偏移项表示“阴影”。通过最初用于解决相关的秩稀疏分解问题的加速近端梯度方法的计算改进来解决相关的优化问题。去除适应图像的色彩偏移会产生增强的图像,其组织学结构之间的色度差异会有所改善。这是通过无参考色彩测量法来验证的,该测量方法是从35个人类肝脏样本和1个被苏木精和曙红染色的小鼠肝脏样本,6个被苏丹III染色的小鼠肝脏样本以及3个被染色的人类肝脏样本估计的用抗CD34单克隆抗体。比色差平均提高了43.86%,99%的置信区间(CI)为[35.35%,51.62%]。此外,根据平均意见评分,在对五位病理学家进行评估的基础上,通过所提出的方法增强的图像显示出平均质量改善了16.60%,其中99%的置信度为[10.46%,22.73%]。

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