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  Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging

Nolte, P., Dullin, C., Svetlove, A., Brettmacher, M., Russmann, C., Schilling, A. F., et al. (2022). Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging. Radiology Research and Practice, 2022: 6765895. doi:10.1155/2022/6765895.

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Nolte, Philipp, Author
Dullin, Christian1, Author           
Svetlove, Angelika, Author
Brettmacher, Marcel, Author
Russmann, Christoph, Author
Schilling, Arndt F., Author
Alves, Frauke1, Author           
Stock, Bernd, Author
Affiliations:
1Research Group of Translational Molecular Imaging, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society, ou_3350306              

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 Abstract: Classical analysis of biological samples requires the destruction of the tissue’s integrity by cutting or grinding it down to thin slices for (Immuno)-histochemical staining and microscopic analysis. Despite high specificity, encoded in the stained 2D section of the whole tissue, the structural information, especially 3D information, is limited. Computed tomography (CT) or magnetic resonance imaging (MRI) scans performed prior to sectioning in combination with image registration algorithms provide an opportunity to regain access to morphological characteristics as well as to relate histological findings to the 3D structure of the local tissue environment. This review provides a summary of prevalent literature addressing the problem of multimodal coregistration of hard- and soft-tissue in microscopy and tomography. Grouped according to the complexity of the dimensions, including image-to-volume (2D ⟶ 3D), image-to-image (2D ⟶ 2D), and volume-to-volume (3D ⟶ 3D), selected currently applied approaches are investigated by comparing the method accuracy with respect to the limiting resolution of the tomography. Correlation of multimodal imaging could position itself as a useful tool allowing for precise histological diagnostic and allow the a priori planning of tissue extraction like biopsies.

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Language(s): eng - English
 Dates: 2022-11-09
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1155/2022/6765895
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Title: Radiology Research and Practice
Source Genre: Journal
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Publ. Info: Hindawi
Pages: - Volume / Issue: 2022 Sequence Number: 6765895 Start / End Page: - Identifier: Other: ISSN
CoNE: https://pure.mpg.de/cone/journals/resource/2090-195X