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Regional registration of whole slide image stacks containing major histological artifacts
BACKGROUND: High resolution 2D whole slide imaging provides rich information about the tissue structure. This information can be a lot richer if these 2D images can be stacked into a 3D tissue volume. A 3D analysis, however, requires accurate reconstruction of the tissue volume from the 2D image sta...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718714/ https://www.ncbi.nlm.nih.gov/pubmed/33276732 http://dx.doi.org/10.1186/s12859-020-03907-6 |
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author | Paknezhad, Mahsa Loh, Sheng Yang Michael Choudhury, Yukti Koh, Valerie Koh Cui Yong, Timothy Tay Kwang Tan, Hui Shan Kanesvaran, Ravindran Tan, Puay Hoon Peng, John Yuen Shyi Yu, Weimiao Tan, Yongcheng Benjamin Loy, Yong Zhen Tan, Min-Han Lee, Hwee Kuan |
author_facet | Paknezhad, Mahsa Loh, Sheng Yang Michael Choudhury, Yukti Koh, Valerie Koh Cui Yong, Timothy Tay Kwang Tan, Hui Shan Kanesvaran, Ravindran Tan, Puay Hoon Peng, John Yuen Shyi Yu, Weimiao Tan, Yongcheng Benjamin Loy, Yong Zhen Tan, Min-Han Lee, Hwee Kuan |
author_sort | Paknezhad, Mahsa |
collection | PubMed |
description | BACKGROUND: High resolution 2D whole slide imaging provides rich information about the tissue structure. This information can be a lot richer if these 2D images can be stacked into a 3D tissue volume. A 3D analysis, however, requires accurate reconstruction of the tissue volume from the 2D image stack. This task is not trivial due to the distortions such as tissue tearing, folding and missing at each slide. Performing registration for the whole tissue slices may be adversely affected by distorted tissue regions. Consequently, regional registration is found to be more effective. In this paper, we propose a new approach to an accurate and robust registration of regions of interest for whole slide images. We introduce the idea of multi-scale attention for registration. RESULTS: Using mean similarity index as the metric, the proposed algorithm (mean ± SD [Formula: see text] ) followed by a fine registration algorithm ([Formula: see text] ) outperformed the state-of-the-art linear whole tissue registration algorithm ([Formula: see text] ) and the regional version of this algorithm ([Formula: see text] ). The proposed algorithm also outperforms the state-of-the-art nonlinear registration algorithm (original: [Formula: see text] , regional: [Formula: see text] ) for whole slide images and a recently proposed patch-based registration algorithm (patch size 256: [Formula: see text] , patch size 512: [Formula: see text] ) for medical images. CONCLUSION: Using multi-scale attention mechanism leads to a more robust and accurate solution to the problem of regional registration of whole slide images corrupted in some parts by major histological artifacts in the imaged tissue. |
format | Online Article Text |
id | pubmed-7718714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77187142020-12-07 Regional registration of whole slide image stacks containing major histological artifacts Paknezhad, Mahsa Loh, Sheng Yang Michael Choudhury, Yukti Koh, Valerie Koh Cui Yong, Timothy Tay Kwang Tan, Hui Shan Kanesvaran, Ravindran Tan, Puay Hoon Peng, John Yuen Shyi Yu, Weimiao Tan, Yongcheng Benjamin Loy, Yong Zhen Tan, Min-Han Lee, Hwee Kuan BMC Bioinformatics Methodology Article BACKGROUND: High resolution 2D whole slide imaging provides rich information about the tissue structure. This information can be a lot richer if these 2D images can be stacked into a 3D tissue volume. A 3D analysis, however, requires accurate reconstruction of the tissue volume from the 2D image stack. This task is not trivial due to the distortions such as tissue tearing, folding and missing at each slide. Performing registration for the whole tissue slices may be adversely affected by distorted tissue regions. Consequently, regional registration is found to be more effective. In this paper, we propose a new approach to an accurate and robust registration of regions of interest for whole slide images. We introduce the idea of multi-scale attention for registration. RESULTS: Using mean similarity index as the metric, the proposed algorithm (mean ± SD [Formula: see text] ) followed by a fine registration algorithm ([Formula: see text] ) outperformed the state-of-the-art linear whole tissue registration algorithm ([Formula: see text] ) and the regional version of this algorithm ([Formula: see text] ). The proposed algorithm also outperforms the state-of-the-art nonlinear registration algorithm (original: [Formula: see text] , regional: [Formula: see text] ) for whole slide images and a recently proposed patch-based registration algorithm (patch size 256: [Formula: see text] , patch size 512: [Formula: see text] ) for medical images. CONCLUSION: Using multi-scale attention mechanism leads to a more robust and accurate solution to the problem of regional registration of whole slide images corrupted in some parts by major histological artifacts in the imaged tissue. BioMed Central 2020-12-04 /pmc/articles/PMC7718714/ /pubmed/33276732 http://dx.doi.org/10.1186/s12859-020-03907-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Paknezhad, Mahsa Loh, Sheng Yang Michael Choudhury, Yukti Koh, Valerie Koh Cui Yong, Timothy Tay Kwang Tan, Hui Shan Kanesvaran, Ravindran Tan, Puay Hoon Peng, John Yuen Shyi Yu, Weimiao Tan, Yongcheng Benjamin Loy, Yong Zhen Tan, Min-Han Lee, Hwee Kuan Regional registration of whole slide image stacks containing major histological artifacts |
title | Regional registration of whole slide image stacks containing major histological artifacts |
title_full | Regional registration of whole slide image stacks containing major histological artifacts |
title_fullStr | Regional registration of whole slide image stacks containing major histological artifacts |
title_full_unstemmed | Regional registration of whole slide image stacks containing major histological artifacts |
title_short | Regional registration of whole slide image stacks containing major histological artifacts |
title_sort | regional registration of whole slide image stacks containing major histological artifacts |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718714/ https://www.ncbi.nlm.nih.gov/pubmed/33276732 http://dx.doi.org/10.1186/s12859-020-03907-6 |
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