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Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images

BACKGROUND: Accurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally sta...

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Autores principales: Liang, Cher-Wei, Chang, Ruey-Feng, Fang, Pei-Wei, Chen, Chiao-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378454/
https://www.ncbi.nlm.nih.gov/pubmed/34476109
http://dx.doi.org/10.4103/jpi.jpi_106_20
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author Liang, Cher-Wei
Chang, Ruey-Feng
Fang, Pei-Wei
Chen, Chiao-Min
author_facet Liang, Cher-Wei
Chang, Ruey-Feng
Fang, Pei-Wei
Chen, Chiao-Min
author_sort Liang, Cher-Wei
collection PubMed
description BACKGROUND: Accurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally stained immunohistochemical (IHC) sections is still challenging. In this study, we aim to assess the feasibility of multidimensional graph-based image registration on aligning serial-section and whole-slide IHC section images. MATERIALS AND METHODS: An automated, patch graph-based registration method was established and applied to align serial, whole-slide IHC sections at ×10 magnification (average 32,947 × 27,054 pixels). The alignment began with the initial alignment of high-resolution reference and translated images (object segmentation and rigid registration) and nonlinear registration of low-resolution reference and translated images, followed by the multidimensional graph-based image registration of the segmented patches, and finally, the fusion of deformed patches for inspection. The performance of the proposed method was formulated and evaluated by the Hausdorff distance between continuous image slices. RESULTS: Sets of average 315 patches from five serial whole slide, IHC section images were tested using 21 different IHC antibodies across five different tissue types (skin, breast, stomach, prostate, and soft tissue). The proposed method was successfully automated to align most of the images. The average Hausdorff distance was 48.93 μm with a standard deviation of 14.94 μm, showing a significant improvement from the previously published patch-based nonlinear image registration method (average Hausdorff distance of 93.89 μm with 50.85 μm standard deviation). CONCLUSIONS: Our method was effective in aligning whole-slide tissue sections at the cell-level resolution. Further advancements in the screening of the proteome topology and 3D tissue reconstruction could be expected.
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spelling pubmed-83784542021-09-01 Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images Liang, Cher-Wei Chang, Ruey-Feng Fang, Pei-Wei Chen, Chiao-Min J Pathol Inform Research Article BACKGROUND: Accurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally stained immunohistochemical (IHC) sections is still challenging. In this study, we aim to assess the feasibility of multidimensional graph-based image registration on aligning serial-section and whole-slide IHC section images. MATERIALS AND METHODS: An automated, patch graph-based registration method was established and applied to align serial, whole-slide IHC sections at ×10 magnification (average 32,947 × 27,054 pixels). The alignment began with the initial alignment of high-resolution reference and translated images (object segmentation and rigid registration) and nonlinear registration of low-resolution reference and translated images, followed by the multidimensional graph-based image registration of the segmented patches, and finally, the fusion of deformed patches for inspection. The performance of the proposed method was formulated and evaluated by the Hausdorff distance between continuous image slices. RESULTS: Sets of average 315 patches from five serial whole slide, IHC section images were tested using 21 different IHC antibodies across five different tissue types (skin, breast, stomach, prostate, and soft tissue). The proposed method was successfully automated to align most of the images. The average Hausdorff distance was 48.93 μm with a standard deviation of 14.94 μm, showing a significant improvement from the previously published patch-based nonlinear image registration method (average Hausdorff distance of 93.89 μm with 50.85 μm standard deviation). CONCLUSIONS: Our method was effective in aligning whole-slide tissue sections at the cell-level resolution. Further advancements in the screening of the proteome topology and 3D tissue reconstruction could be expected. Wolters Kluwer - Medknow 2021-08-03 /pmc/articles/PMC8378454/ /pubmed/34476109 http://dx.doi.org/10.4103/jpi.jpi_106_20 Text en Copyright: © 2021 Journal of Pathology Informatics https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Research Article
Liang, Cher-Wei
Chang, Ruey-Feng
Fang, Pei-Wei
Chen, Chiao-Min
Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images
title Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images
title_full Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images
title_fullStr Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images
title_full_unstemmed Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images
title_short Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images
title_sort improving algorithm for the alignment of consecutive, whole-slide, immunohistochemical section images
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378454/
https://www.ncbi.nlm.nih.gov/pubmed/34476109
http://dx.doi.org/10.4103/jpi.jpi_106_20
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