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dc.contributor.authorChen, Long*
dc.contributor.authorDay, Thomas W.*
dc.contributor.authorTang, Wen*
dc.contributor.authorJohn, Nigel W.*
dc.date.accessioned2017-07-27T10:52:04Z
dc.date.available2017-07-27T10:52:04Z
dc.date.issued2017-11-23
dc.identifier.citationChen, L., Day, T., Tang, W., & John, N.W. (2017). Recent Developments and Future Challenges in Medical Mixed Reality. Proceedings ISMAR 2017, Nantes, France, October 2017.en
dc.identifier.isbn9781538629437
dc.identifier.issnother
dc.identifier.doi10.1109/ISMAR.2017.29
dc.identifier.urihttp://hdl.handle.net/10034/620579
dc.description.abstractMixed Reality (MR) is of increasing interest within technology driven modern medicine but is not yet used in everyday practice. This situation is changing rapidly, however, and this paper explores the emergence of MR technology and the importance of its utility within medical applications. A classification of medical MR has been obtained by applying an unbiased text mining method to a database of 1,403 relevant research papers published over the last two decades. The classification results reveal a taxonomy for the development of medical MR research during this period as well as suggesting future trends. We then use the classification to analyse the technology and applications developed in the last five years. Our objective is to aid researchers to focus on the areas where technology advancements in medical MR are most needed, as well as providing medical practitioners with a useful source of reference.
dc.language.isoenen
dc.relation.urlhttps://ismar2017.sciencesconf.org/en
dc.subjectMixed Realityen
dc.subjectMedicalen
dc.titleRecent Developments and Future Challenges in Medical Mixed Realityen
dc.typeArticleen
dc.contributor.departmentBournemouth University and University of Chesteren
dc.date.accepted2017-07-05
or.grant.openaccessYesen
rioxxterms.funderunfundeden
rioxxterms.identifier.projectunfundeden
rioxxterms.versionAMen
rioxxterms.licenseref.startdate2217-10-31
html.description.abstractMixed Reality (MR) is of increasing interest within technology driven modern medicine but is not yet used in everyday practice. This situation is changing rapidly, however, and this paper explores the emergence of MR technology and the importance of its utility within medical applications. A classification of medical MR has been obtained by applying an unbiased text mining method to a database of 1,403 relevant research papers published over the last two decades. The classification results reveal a taxonomy for the development of medical MR research during this period as well as suggesting future trends. We then use the classification to analyse the technology and applications developed in the last five years. Our objective is to aid researchers to focus on the areas where technology advancements in medical MR are most needed, as well as providing medical practitioners with a useful source of reference.


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