title: Towards automatic bone age estimation from MRI: localization of 3D anatomical landmarks.
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.
authors.forename: Thomas
authors.initials: T
authors.lastname: Ebner
authors.forename: Darko
authors.initials: D
authors.lastname: Stern
authors.forename: Rene
authors.initials: R
authors.lastname: Donner
authors.forename: Horst
authors.initials: H
authors.lastname: Bischof
authors.forename: Martin
authors.initials: M
authors.lastname: Urschler
mesh_terms: D000293:Adolescent; D000365:Age Determination by Skeleton / Q000379:methods*; D000375:Aging / Q000502:physiology*; D059925:Anatomic Landmarks / Q000033:anatomy & histology*; D001185:Artificial Intelligence; D050276:Hand Bones / Q000000981:diagnostic imaging* / Q000502:physiology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult