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Detecting Mammographic Abnormalities from Image Registration Results
Robert Martí, David Raba, Caroline Rubin, Reyer Zwiggelaar
59 - 66
Frontiers in Artificial Intelligence and Applications
Volume 131: Artificial Intelligence Research and Development
Abstract

One of the applications of image registration is to assess object differences from various images that have been spatially correlated. This paper discusses the use of features extracted from subtracted registered images in a classification framework with an aim to detect abnormal mammograms. Both quantitative and qualitative results are provided, which show that although non-optimal classification is obtained, region features extracted after registration can be used to discriminate between normal and abnormal mammograms.

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