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Journal of Digital Imaging

, Volume 31, Issue 6, pp 912–922 | Cite as

Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images

  • G. R. JothilakshmiEmail author
  • Arun Raaza
  • V. Rajendran
  • Y. Sreenivasa Varma
  • R. Guru Nirmal Raj
Article

Abstract

Breast cancer is one of the life-threatening cancers occurring in women. In recent years, from the surveys provided by various medical organizations, it has become clear that the mortality rate of females is increasing owing to the late detection of breast cancer. Therefore, an automated algorithm is needed to identify the early occurrence of microcalcification, which would assist radiologists and physicians in reducing the false predictions via image processing techniques. In this work, we propose a new algorithm to detect the pattern of a microcalcification by calculating its physical characteristics. The considered physical characteristics are the reflection coefficient and mass density of the binned digital mammogram image. The calculation of physical characteristics doubly confirms the presence of malignant microcalcification. Subsequently, by interpolating the physical characteristics via thresholding and mapping techniques, a three-dimensional (3D) projection of the region of interest (RoI) is obtained in terms of the distance in millimeter. The size of a microcalcification is determined using this 3D-projected view. This algorithm is verified with 100 abnormal mammogram images showing microcalcification and 10 normal mammogram images. In addition to the size calculation, the proposed algorithm acts as a good classifier that is used to classify the considered input image as normal or abnormal with the help of only two physical characteristics. This proposed algorithm exhibits a classification accuracy of 99%.

Keywords

Digital mammogram Microcalcification Pattern recognition Binning Reflection coefficient Mass density 3D interpolation Size calculation of microcalcification 

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Copyright information

© Society for Imaging Informatics in Medicine 2018

Authors and Affiliations

  • G. R. Jothilakshmi
    • 1
    Email author
  • Arun Raaza
    • 2
  • V. Rajendran
    • 1
  • Y. Sreenivasa Varma
    • 3
  • R. Guru Nirmal Raj
    • 4
  1. 1.Department of ECEVels UniversityChennaiIndia
  2. 2.Vels UniversityChennaiIndia
  3. 3.Varma Nursing Home and Research CenterChennaiIndia
  4. 4.Department of ECELakshmiammal Polytechnique CollegeKovilpattiIndia

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