Gooßen, AndréAndréGooßenHermann, EugenEugenHermannWeber, Georg MartinGeorg MartinWeberGernoth, ThorstenThorstenGernothPralow, ThomasThomasPralowGrigat, Rolf-RainerRolf-RainerGrigat2021-07-292021-07-292010-11-11Computer Science - Research and Development 26 (1-2): 107-116 (2011-02)http://hdl.handle.net/11420/9998The growth of human bones forms a major problem when automatically segmenting orthopedic radiographs. Any template-based segmentation methods fails to fully capture these non-linear developments. However to extract orthopedic measurements or the bone age for patients of arbitrary age it is mandatory to have a segmentation scheme that deals with growth related changes. In this paper we propose a robust method based on Active Shape Models (ASMs) that on the one hand is invariant against the patient's age and on the other hand generalizes well over the large inter-patient variability. Our method achieves an accuracy of 0.48 mm for adult patients and 0.64 mm for children on a large test set of 180 images, with the patient's age covering a high range from less than one month to 93 years. © 2010 Springer-Verlag.en1865-204220101-2107116SpringerActive shape modelsBone age assessmentDigital radiographyOrthopedicsSegmentationX-rayMedizinConference Paper10.1007/s00450-010-0139-8Conference Paper