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Comparative Study on Various Techniques Involved in Designing a Computer Aided Diagnosis (CAD) System for Mammogram Classification

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • A. R. Mrunalini

    (School of Computing, SASTRA Deemed-to-be-University)

  • A. R. NareshKumar

    (School of Computing, SASTRA Deemed-to-be-University)

  • J. Premaladha

    (School of Computing, SASTRA Deemed-to-be-University)

Abstract

Breast cancer detection can be done using mammography which uses low-dose X-rays to obtain images of the breast in order to detect the abnormalities present in it. Analysing the mammogram can be done by using a Computer Aided Diagnosis (CAD) system to detect abnormalities. Designing a CAD system involves pre-processing, segmentation, feature learning and finally classifying the types of abnormalities using an efficient classifier. This paper compares the various steps and techniques used to design a CAD system and the results obtained are analysed based on their performance. By comparing various methods for pre-processing, segmentation and feature learning, it was found that different methods work well in different contexts. Some of the drawbacks in a few systems are also discussed and future works for further improvements have been suggested.

Suggested Citation

  • A. R. Mrunalini & A. R. NareshKumar & J. Premaladha, 2020. "Comparative Study on Various Techniques Involved in Designing a Computer Aided Diagnosis (CAD) System for Mammogram Classification," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 627-639, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_62
    DOI: 10.1007/978-3-030-41862-5_62
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