Automated bone age assessment using feature extraction

Authors:
Luke M. Davis;Barry-John Theobald;Anthony Bagnall
Affiliations:
School of Computing Sciences, University of East Anglia, Norwich, UK;School of Computing Sciences, University of East Anglia, Norwich, UK;School of Computing Sciences, University of East Anglia, Norwich, UK
Venue:
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Year:
2012

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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.