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X-ray computed tomography and additive manufacturing in medicine: a review

Thompson, Adam; McNally, Donal; Maskery, Ian; Leach, Richard K.

X-ray computed tomography and additive manufacturing in medicine: a review Thumbnail


Authors

DONAL MCNALLY DONAL.MCNALLY@NOTTINGHAM.AC.UK
Professor of Bioengineering



Abstract

The use of X-ray computed tomography (XCT) with additive manufacture (AM) within a medical context is examined in this review. The seven AM process families and various XCT scanning techniques are explained in brief, and the use of these technologies together is detailed over time. The transition of these technologies from a simple method of medical modelling to a robust method of customised implant manufacture is described, and the state-of-the-art for XCT and AM is examined in detail. XCT and AM are identified as having the potential to improve gold standards in both modelling and implant production, and in the conclusions of this review, primary barriers to the increased adoption ofAMand XCT technologies are identified in reference to the main applications of XCT and AM technologies. The primary prohibitive factors generally relate to the cost of production across all of the examined applications, as well as the need for further clinical trials in surgical guidance and applications involving implantation.

Citation

Thompson, A., McNally, D., Maskery, I., & Leach, R. K. (in press). X-ray computed tomography and additive manufacturing in medicine: a review. International Journal of Metrology and Quality Engineering, 8, Article 17. https://doi.org/10.1051/ijmqe/2017015

Journal Article Type Article
Acceptance Date May 2, 2017
Online Publication Date May 30, 2017
Deposit Date Dec 6, 2017
Publicly Available Date Dec 6, 2017
Journal International Journal of Metrology and Quality Engineering
Print ISSN 2107-6839
Electronic ISSN 2107-6847
Publisher EDP Open
Peer Reviewed Peer Reviewed
Volume 8
Article Number 17
DOI https://doi.org/10.1051/ijmqe/2017015
Keywords X-ray computed tomography; Additive manufacture; Modelling
Public URL https://nottingham-repository.worktribe.com/output/862541
Publisher URL https://doi.org/10.1051/ijmqe/2017015

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