Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Anal Cell Pathol (Amst). 2012;35(5-6):407-20. doi: 10.3233/ACP-2012-0069.
In this paper we proposed a multispectral enhancement scheme in which the spectral colors of the stained tissue-structure of interest and its background can be independently modified by the user to further improve their visualization and color discrimination. The colors of the background objects are modified by transforming their N-band spectra through an NxN transformation matrix, which is derived by mapping the representative samples of their original spectra to the spectra of their target colors using least mean square method. On the other hand, the color of the tissue structure of interest is modified by modulating the transformed spectra with the sum of the pixel's spectral residual-errors at specific bands weighted through an NxN weighting matrix; the spectral error is derived by taking the difference between the pixel's original spectrum and its reconstructed spectrum using the first M dominant principal component vectors in principal component analysis. Promising results were obtained on the visualization of the collagen fiber and the non-collagen tissue structures, e.g., nuclei, cytoplasm and red blood cells (RBC), in a hematoxylin and eosin (H&E) stained image.
在本文中，我们提出了一种多光谱增强方案，用户可以通过该方案独立修改感兴趣的染色组织结构及其背景的光谱颜色，以进一步改善它们的可视化和颜色辨别能力。通过对 NxN 变换矩阵进行变换，可以修改背景对象的颜色，该变换矩阵是通过使用最小均方方法将其原始光谱的代表样本映射到目标颜色的光谱来得出的。另一方面，通过使用 NxN 加权矩阵对转换后的光谱进行调制，可以修改感兴趣的组织结构的颜色，该加权矩阵加权了特定波段的像素光谱残差之和；通过使用主成分分析中的前 M 个主成分向量，从像素的原始光谱与其重构光谱之间的差值中得出光谱误差。在苏木精和伊红（H&E）染色图像中，胶原蛋白纤维和非胶原蛋白组织结构（如核、细胞质和红细胞（RBC））的可视化方面取得了有前景的结果。
