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

2004

@inproceedings{RTR2004,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Daniel B. Russakoff and Carlo Tomasi and Torsten Rohlfing
	and Maurer Jr., Calvin R.},
	title =	{Image Similarity Using Mutual Information of Regions},
	booktitle =	{Proceedings of the Eighth European Conference on Computer
	Vision (ECCV 2004)},
	address =	{Prague, Czech Republic},
	pages =	{596--607},
	month =	{May~11--14},
	year =	{2004},
	url =	{http://www.springerlink.com/link.asp?id=njkxc1dge358jfky},
	abstract =	{Mutual information (MI) has emerged in recent years as an
	effective similarity measure for comparing images. One drawback of MI,
	however, is that it is calculated on a pixel by pixel basis, meaning
	that it takes into account only the relationships between corresponding
	individual pixels and not those of each pixels respective neighborhood.
	As a result, much of the spatial information inherent in images is not
	utilized. In this paper, we propose a novel extension to MI called
	regional mutual information (RMI). This extension efficiently takes
	neighborhood regions of corresponding pixels into account. We
	demonstrate the usefulness of RMI by applying it to a real-world
	problem in the medical domain�intensity-based 2D-3D registration of
	X-ray projection images (2D) to a CT image (3D). Using a gold-standard
	spine image data set, we show that RMI is a more robust similarity
	meaure for image registration than MI.},
}