Automated bone age assessment using feature extraction

Luke M. Davis, Barry-John Theobald, Anthony Bagnall

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2012
PublisherSpringer
Pages43-51
Number of pages9
Volume7435
DOIs
Publication statusPublished - 2012

Publication series

NameLecture Notes in Computer Sciences
PublisherSpringer
ISSN (Print)0302-9743

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