On the segmentation and classification of hand radiographs.
This research is part of a wider project to build predictive models of bone age using hand radiograph images. We examine ways of finding the outline of a hand from an X-ray as the first stage in segmenting the image into constituent bones. We assess a variety of algorithms including contouring, which has not previously been used in this context. We introduce a novel ensemble algorithm for combining outlines using two voting schemes, a likelihood ratio test and dynamic time warping (DTW). Our goal is to minimize the human intervention required, hence we investigate alternative ways of training a classifier to determine whether an outline is in fact correct or not. We evaluate outlining and classification on a set of 1370 images. We conclude that ensembling with DTW improves performance of all outlining algorithms, that the contouring algorithm used with the DTW ensemble performs the best of those assessed, and that the most effective classifier of hand outlines assessed is a random forest applied to outlines transformed into principal components.
School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, NR4 7TJ, United Kingdom. luke.davis@uea.ac.uk
Luke M
LM
Davis
Barry-John
BJ
Theobald
Jason
J
Lines
Andoni
A
Toms
Anthony
A
Bagnall
D000365:Age Determination by Skeleton / Q000145:classification* / Q000379:methods*; D000375:Aging / Q000502:physiology; D000465:Algorithms; D001185:Artificial Intelligence; D001331:Automation; D002648:Child; D005260:Female; D005385:Fingers / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D005583:Fourier Analysis; D006225:Hand / Q000000981:diagnostic imaging*; D050276:Hand Bones / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016013:Likelihood Functions; D008297:Male; D025341:Principal Component Analysis; D012015:Reference Standards; D012984:Software; D014965:X-Rays