Automated bone age assessment using feature extraction

Davis, Luke M., Theobald, Barry-John and Bagnall, Anthony (2012) Automated bone age assessment using feature extraction. In: Intelligent Data Engineering and Automated Learning - IDEAL 2012. Lecture Notes in Computer Sciences, 7435 . Springer, pp. 43-51.

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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.

Item Type:	Book Section
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Data Science and Statistics
Depositing User:	Users 2731 not found.
Date Deposited:	12 Sep 2012 11:34
Last Modified:	23 Apr 2023 01:47
URI:	https://ueaeprints.uea.ac.uk/id/eprint/39533
DOI:	10.1007/978-3-642-32639-4_6

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