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Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation

PURPOSE: Histopathological imaging is widely used for the analysis and diagnosis of multiple diseases. Several methods have been proposed for the 3D reconstruction of pathological images, captured from thin sections of a given specimen, which get nonlinearly deformed due to the preparation process....

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Autores principales: Kugler, Mauricio, Goto, Yushi, Tamura, Yuki, Kawamura, Naoki, Kobayashi, Hirokazu, Yokota, Tatsuya, Iwamoto, Chika, Ohuchida, Kenoki, Hashizume, Makoto, Shimizu, Akinobu, Hontani, Hidekata
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858398/
https://www.ncbi.nlm.nih.gov/pubmed/31267332
http://dx.doi.org/10.1007/s11548-019-02019-8
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author Kugler, Mauricio
Goto, Yushi
Tamura, Yuki
Kawamura, Naoki
Kobayashi, Hirokazu
Yokota, Tatsuya
Iwamoto, Chika
Ohuchida, Kenoki
Hashizume, Makoto
Shimizu, Akinobu
Hontani, Hidekata
author_facet Kugler, Mauricio
Goto, Yushi
Tamura, Yuki
Kawamura, Naoki
Kobayashi, Hirokazu
Yokota, Tatsuya
Iwamoto, Chika
Ohuchida, Kenoki
Hashizume, Makoto
Shimizu, Akinobu
Hontani, Hidekata
author_sort Kugler, Mauricio
collection PubMed
description PURPOSE: Histopathological imaging is widely used for the analysis and diagnosis of multiple diseases. Several methods have been proposed for the 3D reconstruction of pathological images, captured from thin sections of a given specimen, which get nonlinearly deformed due to the preparation process. The majority of the available methods for registering such images use the degree of matching of adjacent images as the criteria for registration, which can result in unnatural deformations of the anatomical structures. Moreover, most methods assume that the same staining is used for all images, when in fact multiple staining is usually applied in order to enhance different structures in the images. METHODS: This paper proposes a non-rigid 3D reconstruction method based on the assumption that internal structures on the original tissue must be smooth and continuous. Landmarks are detected along anatomical structures using template matching based on normalized cross-correlation (NCC), forming jagged shape trajectories that traverse several slices. The registration process smooths out these trajectories and deforms the images accordingly. Artifacts are automatically handled by using the confidence of the NCC in order to reject unreliable landmarks. RESULTS: The proposed method was applied to a large series of histological sections from the pancreas of a KPC mouse. Some portions were dyed primarily with HE stain, while others were dyed alternately with HE, CK19, MT and Ki67 stains. A new evaluation method is proposed to quantitatively evaluate the smoothness and isotropy of the obtained reconstructions, both for single and multiple staining. CONCLUSIONS: The experimental results show that the proposed method produces smooth and nearly isotropic 3D reconstructions of pathological images with either single or multiple stains. From these reconstructions, microanatomical structures enhanced by different stains can be simultaneously observed.
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spelling pubmed-68583982019-12-03 Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation Kugler, Mauricio Goto, Yushi Tamura, Yuki Kawamura, Naoki Kobayashi, Hirokazu Yokota, Tatsuya Iwamoto, Chika Ohuchida, Kenoki Hashizume, Makoto Shimizu, Akinobu Hontani, Hidekata Int J Comput Assist Radiol Surg Original Article PURPOSE: Histopathological imaging is widely used for the analysis and diagnosis of multiple diseases. Several methods have been proposed for the 3D reconstruction of pathological images, captured from thin sections of a given specimen, which get nonlinearly deformed due to the preparation process. The majority of the available methods for registering such images use the degree of matching of adjacent images as the criteria for registration, which can result in unnatural deformations of the anatomical structures. Moreover, most methods assume that the same staining is used for all images, when in fact multiple staining is usually applied in order to enhance different structures in the images. METHODS: This paper proposes a non-rigid 3D reconstruction method based on the assumption that internal structures on the original tissue must be smooth and continuous. Landmarks are detected along anatomical structures using template matching based on normalized cross-correlation (NCC), forming jagged shape trajectories that traverse several slices. The registration process smooths out these trajectories and deforms the images accordingly. Artifacts are automatically handled by using the confidence of the NCC in order to reject unreliable landmarks. RESULTS: The proposed method was applied to a large series of histological sections from the pancreas of a KPC mouse. Some portions were dyed primarily with HE stain, while others were dyed alternately with HE, CK19, MT and Ki67 stains. A new evaluation method is proposed to quantitatively evaluate the smoothness and isotropy of the obtained reconstructions, both for single and multiple staining. CONCLUSIONS: The experimental results show that the proposed method produces smooth and nearly isotropic 3D reconstructions of pathological images with either single or multiple stains. From these reconstructions, microanatomical structures enhanced by different stains can be simultaneously observed. Springer International Publishing 2019-07-02 2019 /pmc/articles/PMC6858398/ /pubmed/31267332 http://dx.doi.org/10.1007/s11548-019-02019-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Kugler, Mauricio
Goto, Yushi
Tamura, Yuki
Kawamura, Naoki
Kobayashi, Hirokazu
Yokota, Tatsuya
Iwamoto, Chika
Ohuchida, Kenoki
Hashizume, Makoto
Shimizu, Akinobu
Hontani, Hidekata
Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
title Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
title_full Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
title_fullStr Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
title_full_unstemmed Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
title_short Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
title_sort robust 3d image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858398/
https://www.ncbi.nlm.nih.gov/pubmed/31267332
http://dx.doi.org/10.1007/s11548-019-02019-8
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