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A model-based framework for the detection of spiculated lesions on mammography
M.P. Sampat, A.C. Bovik, M.K. Markey and G.J. Whitman
Medical Physics
Abstract
The detection of lesions on mammography is a repetitive and fatiguing task. Thus, computer-aided
detection systems have been developed to aid radiologists. The detection accuracy of current systems
is much higher for clusters of microcalcifications than for spiculated masses. In this article, the
authors present a new model-based framework for the detection of spiculated masses. The authors
have invented a new class of linear filters, spiculated lesion filters, for the detection of converging
lines or spiculations. These filters are highly specific narrowband filters, which are designed to
match the expected structures of spiculated masses. As a part of this algorithm, the authors have
also invented a novel technique to enhance spicules on mammograms. This entails filtering in the
radon domain. They have also developed models to reduce the false positives due to normal linear
structures. A key contribution of this work is that the parameters of the detection algorithm are
based on measurements of physical properties of spiculated masses. The results of the detection
algorithm are presented in the form of free-response receiver operating characteristic curves on
images from the Mammographic Image Analysis Society and Digital Database for Screening Mammography
databases.
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