Roberts, N, Magee, D, Song, Y et al. (7 more authors) (2012) Towards Routine Use of 3D Histopathology As a Research Tool. American Journal of Pathology, 180 (5). 1835 - 1842. ISSN 0002-9440
Abstract
Three-dimensional (3D) reconstruction and examination of tissue at microscopic resolution have significant potential to enhance the study of both normal and disease processes, particularly those involving structural changes or those in which the spatial relationship of disease features is important. Although other methods exist for studying tissue in 3D, using conventional histopathological features has significant advantages because it allows for conventional histopathological staining and interpretation techniques. ntil now, its use has not been routine in esearch because of the technical difficulty in constructing D tissue models. We describe a novel system or 3D histological reconstruction, integrating hole-slide imaging (virtual slides), image serving, registration, and visualization into one user-friendly package. It produces high-resolution 3D reconstructions with minimal user interaction and can be used in a histopathological laboratory without input from computing specialists. It uses a novel method for slice-to-slice image registration using automatic registration algorithms custom designed for both virtual slides and histopathological images. This system has been applied to >300 separate 3D volumes from eight different tissue types, using a total of 5500 virtual slides comprising 1.45 TB of primary image data. Qualitative and quantitative metrics for the accuracy of 3D reconstruction are provided, with measured registration accuracy approaching 120 m for a 1-cm piece of tissue. Both 3D tissue volumes and generated 3D models are presented for four demonstrator cases.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012, Elsevier. This is an author produced version of a paper published in American Journal of Pathology. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Pathology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Jun 2013 10:44 |
Last Modified: | 29 Mar 2018 17:13 |
Published Version: | http://dx.doi.org/10.1016/j.ajpath.2012.01.033 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ajpath.2012.01.033 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75791 |