van de Lande, LS;
Papaioannou, A;
Dunaway, DJ;
(2019)
Geometric morphometrics aided by machine learning in craniofacial surgery.
Journal of Orthodontics
, 46
(1)
pp. 81-83.
10.1177/1465312519840030.
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Abstract
Geometric morphometrics aided by machine learning provide detailed and accurate statistical models of facial form. They promise to be extremely effective tools in surgical planning and assessment; however, a clinical tool to use this information is still to be created.
| Type: | Article |
|---|---|
| Title: | Geometric morphometrics aided by machine learning in craniofacial surgery |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/1465312519840030 |
| Publisher version: | https://doi.org/10.1177%2F1465312519840030 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | craniofacial surgery, Large Scale Face Model, morphometrics, statistical shape modelling |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Developmental Biology and Cancer Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10079155 |
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