Localization of Eosinophilic Esophagitis from H&E stained images using multispectral imaging

This study is an initial investigation on the capability of multispectral imaging to capture subtle spectral information that would enable the automatic delineation between the eosinophilic esophagitis and other eosin stained tissue components, especially the RBCs. In the method, a principal component analysis (PCA) was performed on the spectral transmittance samples of the different tissue components, excluding however the transmittance samples of the eosinophilic esophagitis. From the average spectral error configuration of the eosinophilic esophagitis transmittance samples, i.e. the difference between the actual transmittance and the estimated transmittance using m PC vectors, we indentified two spectral bands by which we can localize the eosinophils. Initial results show the possibility of automatically localizing the eosinophilic esophagitis by utilizing spectral information

Multispectral Enhancement Method to Increase the Visual Differences of Tissue Structures in Stained Histopathology Images

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

Multispectral Enhancement towards Digital Staining

Background:: Digital staining can be considered as a special form of image enhancement wherein the concern is not only to increase the contrast between the background objects and objects of interest, but to also impart the colors that mark the objects’ unique reactions to a specific stain. In this paper, we extended the previously proposed multispectral enhancement methods such that the colors of the background pixels can also be changed. Methods:: In the previous multispectral enhancement methods a shifting factor is provided to the original spectrum. To implement digital staining, a spectral transformation process is introduced prior to spectral shifting. Results:: The enhancement method is applied to multispectral images of H&E stained liver tissue. The resulting digitally stained images show good correlation with the serial-section images of the tissue which are physically stained with Masson's trichrome. Conclusion:: We have presented a multispectral enhancement method that can be adjusted to produce digitally stained-images. The current experimental results show the viability of the method. However, to achieve robust enhancement performance issues that arise from variations in staining conditions has to be addressed as well. This would be part of our future work

Improving the visualization and detection of tissue folds in whole slide images through color enhancement

Objective : The objective of this paper is to improve the visualization and detection of tissue folds, which are prominent among tissue slides, from the pre-scan image of a whole slide image by introducing a color enhancement method that enables the differentiation between fold and non-fold image pixels. Method: The weighted difference between the color saturation and luminance of the image pixels is used as shifting factor to the original RGB color of the image. Results: Application of the enhancement method to hematoxylin and eosin (H&E) stained images improves the visualization of tissue folds regardless of the colorimetric variations in the images. Detection of tissue folds after application of the enhancement also improves but the presence of nuclei, which are also stained dark like the folds, was found to sometimes affect the detection accuracy. Conclusion: The presence of tissue artifacts could affect the quality of whole slide images, especially that whole slide scanners select the focus points from the pre-scan image wherein the artifacts are indistinguishable from real tissue area. We have a presented in this paper an enhancement scheme that improves the visualization and detection of tissue folds from pre-scan images. Since the method works on the simulated pre-scan images its integration to the actual whole slide imaging process should also be possible

Multispectral Enhancement Method to Increase the Visual Differences of Tissue Structures in Stained Histopathology Images

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

Multispectral Enhancement towards Digital Staining

Background: Digital staining can be considered as a special form of image enhancement wherein the concern is not only to increase the contrast between the background objects and objects of interest, but to also impart the colors that mark the objects’ unique reactions to a specific stain. In this paper, we extended the previously proposed multispectral enhancement methods such that the colors of the background pixels can also be changed

Color standardization in whole slide imaging using a color calibration slide

Background: Color consistency in histology images is still an issue in digital pathology. Different imaging systems reproduced the colors of a histological slide differently. Materials and Methods: Color correction was implemented using the color information of the nine color patches of a color calibration slide. The inherent spectral colors of these patches along with their scanned colors were used to derive a color correction matrix whose coefficients were used to convert the pixels′ colors to their target colors. Results: There was a significant reduction in the CIELAB color difference, between images of the same H & E histological slide produced by two different whole slide scanners by 3.42 units, P < 0.001 at 95% confidence level. Conclusion: Color variations in histological images brought about by whole slide scanning can be effectively normalized with the use of the color calibration slide