Literature DB >> 22935779

Multispectral enhancement method to increase the visual differences of tissue structures in stained histopathology images.

Pinky A Bautista1, Yukako Yagi.   

Abstract

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.

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Mesh:

Year:  2012        PMID: 22935779      PMCID: PMC4605764          DOI: 10.3233/ACP-2012-0069

Source DB:  PubMed          Journal:  Anal Cell Pathol (Amst)        ISSN: 2210-7177            Impact factor:   2.916


  3 in total

1.  Staining correction in digital pathology by utilizing a dye amount table.

Authors:  Pinky A Bautista; Yukako Yagi
Journal:  J Digit Imaging       Date:  2015-06       Impact factor: 4.056

2.  Context-free hyperspectral image enhancement for wide-field optical biomarker visualization.

Authors:  Arturo Pardo; José A Gutiérrez-Gutiérrez; José M López-Higuera; Olga M Conde
Journal:  Biomed Opt Express       Date:  2019-12-09       Impact factor: 3.732

3.  Segmentation and Recognition of the Pathological Features of Squamous Cell Carcinoma of the Skin Based on Multispectral Imaging.

Authors:  Cheng Wang; Qi Chen; Tijie Gao; Shijun Guo; Huazhong Xiang; Gang Zheng; Dawei Zhang; Xiuli Wang
Journal:  J Clin Med       Date:  2022-07-01       Impact factor: 4.964

  3 in total

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