Refereed full papers (journals, book chapters, international conferences)

2004

@article{ALL2004,
	vgclass =	{refpap},
	author =	{Sameer Antani and D. J. Lee and Long, L. Rodney and
	George R. Thoma},
	title =	{Evaluation of shape similarity measurement methods for
	spine X-ray images},
	journal =	{Journal of Visual Communication and Image Representation},
	volume =	{15},
	number =	{3},
	pages =	{285--302},
	month =	{September},
	year =	{2004},
	url =	{http://dx.doi.org/10.1016/j.jvcir.2004.04.005},
	abstract =	{Efficient content-based image retrieval (CBIR) of
	biomedical images is a challenging problem. Feature representation
	algorithms used in indexing medical images on the pathology of interest
	have to address conflicting goals of reducing feature dimensionality
	while retaining important and often subtle biomedical features. At the
	Lister Hill National Center for Biomedical Communications, an
	intramural R\&D division of the U.S. National Library of Medicine, we
	are developing CBIR prototype for digitized images of a collection of
	17,000 cervical and lumbar spine X-rays taken as a part of the second
	National Health and Nutrition Examination Survey (NHANES II). The
	vertebra shape effectively describes various pathologies identified by
	medical experts as being consistently and reliably found in the image
	collection. A suitable shape algorithm must represent shapes in low
	dimension, be invariant to rotation, translation, and scale transforms,
	and retain relevant pathology. Additionally, supported similarity
	algorithms must be useful in retrieving images that are relevant to the
	queries posed by the intended target community, viz. medical
	researchers, physicians, etc. This paper describes an evaluation of two
	popular shape similarity methods from the literature on a set of 250
	vertebra boundary shapes. The polygon approximation method achieved a
	performance score of 55.94\% and bettered the Fourier descriptor
	algorithm which had a performance score of 46.96\%.},
}