A new fourier-based approach to measure irregularity of breast masses in mammograms

Gensheng Zhang, Sung Shin, Wei Wang, Carrie Hruska, Hyung D. Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Morphologic appearance is one of intuitive diagnosis factors of mass lesions in breast imaging, and irregular shape is one of the most frequent appearances for malignant masses. Thus, an effective measure of morphological irregularity will provide a helpful reference to determine malignancy of breast masses. In this paper, a new measure based on Fourier Transform, named Fourier Irregularity Index (FII), was developed to provide a reliable malignant/benign classification factor. The experiment was conducted with 418 breast masses, including 190 malignant cases and 218 benign cases. Performance was assessed and compared among various methods using Receiver Operating Characteristics (ROC) analysis. The proposed measure in this study achieved malignant/benign classification accuracy of 96% with an area (Az) of 0.99 under the receiver operating characteristics (ROC) curve, which outperformed typical traditional approaches, such as Compactness (accuracy of 90%, Az = 0.96), Fractal Dimension (accuracy of 90%, Az = 0.95), Fourier Factor (accuracy of 90%, Az = 0.97), and Fractional Concavity (accuracy of 75%, A z = 0.65).

Original languageEnglish (US)
Title of host publicationProceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012
Pages153-157
Number of pages5
DOIs
StatePublished - 2012
Event2012 ACM Research in Applied Computation Symposium, RACS 2012 - San Antonio, TX, United States
Duration: Oct 23 2012Oct 26 2012

Publication series

NameProceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012

Other

Other2012 ACM Research in Applied Computation Symposium, RACS 2012
Country/TerritoryUnited States
CitySan Antonio, TX
Period10/23/1210/26/12

Keywords

  • Fourier irregularity index
  • Irregularity measure
  • Shape factor

ASJC Scopus subject areas

  • Computational Theory and Mathematics

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