Automated Classification of Breast Cancer Lesions for Digitised Mammograms via Computer-Aided Diagnosis System

Authors

  • Saifullah Harith Suradi School of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin (UniSZA), 21300 Kuala Nerus, Terengganu, Malaysia
  • Kamarul Amin Abdullah School of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin (UniSZA), 21300 Kuala Nerus, Terengganu, Malaysia & Medical Imaging Research Group (MIRG), Faculty of Health Sciences, Universiti Sultan Zainal Abidin (UniSZA), 21300 Kuala Nerus, Terengganu, Malaysia
  • Nor Ashidi Mat Isa School of Electrical and Electronic Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia

DOI:

https://doi.org/10.33736/jaspe.3517.2021

Keywords:

Breast imaging, Computed aided diagnosis, Medical image processing, medical imaging

Abstract

Women with breast cancer have a high risk of death. Digitised mammograms can be used to detect the early stage of breast cancer. However, digitised mammograms suffer low contrast appearances that may lead to misdiagnosis. This paper proposes a Computer-Aided Diagnosis (CAD) system of automated classification of breast cancer lesions using a modified image processing technique of Fuzzy Anisotropic Diffusion Histogram Equalization Contrast Adaptive Limited (FADHECAL) incorporated with Multilevel Otsu Thresholding on digitised mammograms. Four main blocks were used in this CAD system, namely; (i) Pre-processing and Enhancement block; (ii) Segmentation block; (iii) Region of Interests (ROIs) Extraction block; and (iv) Classification block. The CAD system was tested on 30 digitised mammograms retrieved from the Mini-Mammographic Image Analysis Society (MIAS) database with various degrees of severity and background tissues. The proposed CAD system showed a high accuracy of 96.67% for the detection of breast cancer lesions.

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Journal of Applied Science & Process Engineering, Volume 8, Number 2, 2021

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Published

2021-10-31

How to Cite

Suradi, S. H., Abdullah, K. A., & Isa, N. A. M. . (2021). Automated Classification of Breast Cancer Lesions for Digitised Mammograms via Computer-Aided Diagnosis System. Journal of Applied Science &Amp; Process Engineering, 8(2), 892–902. https://doi.org/10.33736/jaspe.3517.2021

Issue

Vol. 8 No. 2 (2021): Journal of Applied Science & Process Engineering, Volume 8, Number 2, 2021

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Articles

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