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A Detail Process for CAD Based Breast Cancer Detection

Authors

  • Priyanka Banerjee

    Department of Computer Science, The Bhawanipur Education Society College, Kolkata, India

  • Samir Kumar Bandyopadhyay

    Academic Advisor, The Bhawanipur Education Society College, Kolkata, India

DOI:

https://doi.org/10.30683/1929-2279.2019.08.03

Keywords:

Breast cancer, mammography, risk factors, Pectoral Muscle.

Abstract

Breast cancer is known to cause high mortality unless detected in time. Early detection during the onset of the disease can prevent mortality. Early detection can prevent the spreading of the disease thus providing a healthy life to senior citizens. Mammographic screening and surgical biopsy will yield huge number of images to be deciphered by radiologists and pathologists respectively. MIAS dataset is sufficiently large to conduct experimental analysis. Moreover, the dataset contains 322 mammogram images of different size, shape and morphology. This paper discussed about breast cancer detection and diagnosis process. (Word count -91 words).

References

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American Cancer Society. Breast Cancer Facts & Figures 2019-2020. American Cancer Society 2019; pp. 1-44. https://doi.org/10.1007/978-1-4614-6439-6_151-2

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Oliveira HCR, de Mencattini A, Casti P, Martinelli E, Natale C di Catani JH, Vieira MAC. Reduction of false-positives in a CAD scheme for automated detection of architectural distortion in digital mammography. SPIE Medical Imaging 2018. Retrieved from https://www.spiedigitallibrary. org/conference-proceedings-of-spie/10575/105752P/ Reduction-of-false-positives-in-a-CAD-scheme-for-automated/10.1117/12.2293388.short?tab=ArticleLink

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Published

2019-12-31

Issue

Vol. 8 No. 1 (2019)

Section

Articles

How to Cite

A Detail Process for CAD Based Breast Cancer Detection . (2019). Journal of Cancer Research Updates, 8(1), 14-21. https://doi.org/10.30683/1929-2279.2019.08.03

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