IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v152y2021ics096007792100655x.html
   My bibliography  Save this article

Multifractal theory based breast tissue characterization for early detection of breast cancer

Author

Listed:
  • Joseph, Annie Julie
  • Pournami, P.N.

Abstract

Mammography has proven to be the most effective tool for detecting breast cancer in its earliest and treatable stage. This paper investigates various phases of mammogram image analysis and different abnormality detection techniques in the mammogram. The present study’s primary aim is to apply the Multifractal theory for the analysis of digital mammograms. The mammogram images are x-raying images of the breast and grayscale in nature. The grayscale mammogram images are processed using image processing techniques and then analyzed by multifractal characteristics. Initially, simple thresholding used to avoid artefacts and noises in the mammograms taken from the MIAS dataset of 322 images. The thresholded images resulted in sharp edges and hence smoothened using a Gaussian filter of appropriate configuration. A novel feature extraction method is proposed based on multifractal spectral parameters. The multifractal characteristics of each mammogram plotted, and multifractal features extracted from the spectrum. The major multifractal features are the bandwidth of the spectrum, the height of the spectrum, maximum and minimum singularity exponent, peak singularity exponent, and the strength of multifractality. Out of the chosen multifractal features, the width of the spectrum, the height of the spectrum, minimum value for the strength of multifractality found to be the most significant features after conducting statistical analysis using ANOVA (Analysis of Variance). We propose a novel lesion localization method based on the extracted multifractal spectral parameters. The pectoral muscle present in the mammogram removed, and the mammogram image divided into four quadrants. The lesion or mass location in a specific quadrant is identified based on the variation in the quadrant’s multifractal characteristics. This method will reduce the search space of lesion in a single mammogram. Thus, the present study revealed that mammogram images exhibit multifractal behaviour. The multifractal parameters appear to be valuable biomarkers for quantitative assessment of breast tissue in the mammogram, which helps to diagnose breast cancer in its early stage.

Suggested Citation

  • Joseph, Annie Julie & Pournami, P.N., 2021. "Multifractal theory based breast tissue characterization for early detection of breast cancer," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
  • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s096007792100655x
    DOI: 10.1016/j.chaos.2021.111301
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007792100655X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2021.111301?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Song, Zhijun & Jin, Wenxuan & Jiang, Guanghui & Li, Sichun & Ma, Wenqiu, 2021. "Typical and atypical multifractal systems of urban spaces—using construction land in Zhengzhou from 1988 to 2015 as an example," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    2. Stojić, Tomislav & Reljin, Irini & Reljin, Branimir, 2006. "Adaptation of multifractal analysis to segmentation of microcalcifications in digital mammograms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 494-508.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Reljin, Irini S. & Reljin, Branimir D. & Avramov-Ivić, Milka L. & Jovanović, Dušan V. & Plavec, Goran I. & Petrović, Slobodan D. & Bogdanović, Gordana M., 2008. "Multifractal analysis of the UV/VIS spectra of malignant ascites: Confirmation of the diagnostic validity of a clinically evaluated spectral analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3563-3573.
    2. Shi, Wen & Zou, Rui-biao & Wang, Fang & Su, Le, 2015. "A new image segmentation method based on multifractal detrended moving average analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 197-205.
    3. García-Rojas, Blanca E. & Ramirez-Dámaso, Gabriel & Caballero, Francisco & Femat, Ricardo, 2022. "Crisis-induced intermittency in Mexican dam flows," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s096007792100655x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.