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A Model for Diagnosing Breast Cancerous Tissue from Thermal Images Using Active Contour and Lyapunov Exponent

Hossein Ghayoumi Zadeh,Javad Haddadnia,Alimohammad Montazeri

Published 2016 in Iranian Journal of Public Health

ABSTRACT

Background: The segmentation of cancerous areas in breast images is important for the early detection of disease. Thermal imaging has advantages, such as being non-invasive, non-radiation, passive, quick, painless, inexpensive, and non-contact. Imaging technique is the focus of this research. Methods: The proposed model in this paper is a combination of surf and corners that are very resistant. Obtained features are resistant to changes in rotation and revolution then with the help of active contours, this feature has been used for segmenting cancerous areas. Results: Comparing the obtained results from the proposed method and mammogram show that proposed method is Accurate and appropriate. Benign and malignance of segmented areas are detected by Lyapunov exponent. Values obtained include TP=91.31%, FN=8.69%, FP=7.26%. Conclusion: The proposed method can classify those abnormally segmented areas of the breast, to the Benign and malignant cancer.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    Iranian Journal of Public Health

  • Publication date

    2016-05-01

  • Fields of study

    Medicine, Computer Science, Engineering

  • Identifiers
    PMID 27398339PMCID 4935710
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar, PubMed

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