dc.contributor.author |
Unterpirker, Walter |
|
dc.contributor.author |
Ebner, Thomas |
|
dc.contributor.author |
Stern, Darko |
|
dc.contributor.author |
Urschler, Martin |
|
dc.coverage.spatial |
Lincoln, UK |
|
dc.date.accessioned |
2021-08-04T22:49:31Z |
|
dc.date.available |
2021-08-04T22:49:31Z |
|
dc.date.issued |
2015 |
|
dc.identifier.citation |
Editors: Lambrou, Tryphon, Ye, Xujiong. Medical Image Understanding and Analysis 2015. BMVA. 195-200. 2015 |
|
dc.identifier.uri |
https://hdl.handle.net/2292/55843 |
|
dc.description.abstract |
Radiological age estimation of living subjects from MR images has recently become very popular. Besides skeletal ossification this can be done using the mineralization status of wisdom teeth. To support potential automatic age estimation, an important preliminary step is a reliable and automatic localization of the wisdom teeth. Therefore, we propose a random regression forest framework to localize third molars, which is capable to predict landmarks up to an error of 3.55 ± 2.62 mm in mean and standard deviation in a challenging 3D MRI dataset. |
|
dc.relation.ispartof |
19th Int Conference on Medical Image Understanding and Analysis |
|
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
|
dc.title |
Automatic third molar localization from 3D MRI using random regression forests |
|
dc.type |
Conference Item |
|
pubs.begin-page |
195 |
|
dc.date.updated |
2021-07-04T00:55:07Z |
|
dc.rights.holder |
Copyright: The authors |
en |
pubs.end-page |
200 |
|
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Conference Paper |
|
pubs.elements-id |
858348 |
|