Abstract
Bone age assessment is a task performed daily in hospitals worldwide, this involves a clinician estimating the age of a patient from a radiograph of the non-dominant hand. In this paper, we propose a combination of image processing and feature extraction algorithms to automatically predict the Tanner-Whitehouse bone stage, the assessment standard used in forming bone age estimates.
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Davis, L.M., Theobald, BJ., Bagnall, A. (2012). Automated Bone Age Assessment Using Feature Extraction. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_6
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DOI: https://doi.org/10.1007/978-3-642-32639-4_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32638-7
Online ISBN: 978-3-642-32639-4
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