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. © 2012 Springer-Verlag.
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CITATION STYLE
Davis, L. M., Theobald, B. J., & Bagnall, A. (2012). Automated bone age assessment using feature extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7435 LNCS, pp. 43–51). https://doi.org/10.1007/978-3-642-32639-4_6
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