A Wavelet CFAR Detector For Mass Detection In Mammography

Abstract

We introduce a continuous scale wavelet detector for identifying masses (possible breast cancers) in mammograms. Continuous-scale wavelet algorithms have been discussed in the past, however this is the first reported algorithm that uses a scaled version of the same mother wavelet at each scale of analysis. This single mother wavelet property leads to a simpler implementation and a more direct application of detection theory to recognition problems than traditional multiscale analysis. In addition, we show that a continuous-scale search is necessary for computer aided diagnosis of mammography since traditional solutions using dyadic scales (powers of two) either fail to detect some masses or signal too many false alarms. Our novel wavelet detector combines a wavelet formulation with the classical theory of constant false alarm rates (CFAR) detectors. Finally, we show that our algorithm is able to detect masses in actual mammograms that could not be seen using conventional windowing and leveling or other traditional methods of contrast enhancement.

Department(s)

Electrical and Computer Engineering

Comments

National Science Foundation, Grant DAMD17-93-J-3003

Keywords and Phrases

Digital mammography; Image processing; Multiscale representations; Wavelet analysis

International Standard Serial Number (ISSN)

1996-756X; 0277-786X

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Society of Photo-optical Instrumentation Engineers, All rights reserved.

Publication Date

26 Mar 1998

Link to Full Text

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