Feature coincidence trees for registration of ultrasound breast images

Registration of an image, the query or reference, to a database of rotated and translated exemplars constitutes an important image retrieval and indexing application which arises in biomedical imaging, digital libraries, georegistration, and other areas. Two important issues are the specification of a class of discriminatory and generalizable image features and determination of an appropriate image-dissimilarity measure to rank the closeness of the query image with respect to images in the database. The theoretically best set of features and dissimilarity measure are those which can be implemented with the lowest misregistration error rate. In this paper we study a method based on feature discrimination using feature coincidence trees and mutual ?-information measures of feature correlation. Feature coincidence trees represent the commonality between pairs of images using joint histograms of many simple features, or tags, which are organized in a data structure similar to that Amit and...

• Type: Conference
• Year: 2001
• Where: ICIP
• Authors: Huzefa Neemuchwala, Alfred O. Hero, Paul L. Carson
• Keywords: Feature Coincidence Trees, ICIP 2001, Image Processing, Joint Histograms, Mutual Alpha-information Measure