@inbook{
 type = {inbook},
 year = {2014},
 pages = {421-428},
 volume = {17},
 websites = {http://link.springer.com/10.1007/978-3-319-10470-6_53},
 publisher = {Springer, Cham},
 city = {Boston},
 id = {fb447509-87be-3c9a-b846-24b48fad474a},
 created = {2015-02-18T08:46:00.000Z},
 file_attached = {false},
 profile_id = {53d1e3c7-2f16-3c81-9a84-dccd45be4841},
 last_modified = {2019-11-08T01:40:14.497Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Ebner2014},
 folder_uuids = {0ec41d70-75f1-4a99-820b-0a83ccc37f54},
 private_publication = {false},
 abstract = {Bone age estimation (BAE) is an important procedure in forensic practice which recently has seen a shift in attention from X-ray to MRI based imaging. To automate BAE from MRI, localization of the joints between hand bones is a crucial first step, which is challenging due to anatomical variations, different poses and repeating structures within the hand. We propose a landmark localization algorithm using multiple random regression forests, first analyzing the shape of the hand from information of the whole image, thus implicitly modeling the global landmark configuration, followed by a refinement based on more local information to increase prediction accuracy. We are able to clearly outperform related approaches on our dataset of 60 T1-weighted MR images, achieving a mean landmark localization error of 1.4 ?? 1.5mm, while having only 0.25% outliers with an error greater than 10mm.},
 bibtype = {inbook},
 author = {Ebner, Thomas and Stern, Darko and Donner, Rene and Bischof, Horst and Urschler, Martin},
 editor = {Golland, P. and Hata, N. and Barillot, C. and Hornegger, J. and Howe, R.},
 doi = {10.1007/978-3-319-10470-6_53},
 chapter = {Towards Automatic Bone Age Estimation from MRI: Localization of 3D Anatomical Landmarks},
 title = {Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention}
}

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