Classification of abnormalities in mammograms by new asymmetric fractal features

• Autorzy: Beheshti S. M. A. , Noubari H. A. , Fatemizadeh E. , Khalili M.

Identyfikatory

DOI

10.1016/j.bbe.2015.07.002

• Języki publikacji: EN

Abstrakty

EN

In this paper we use fractal method for detection and diagnosis of abnormalities in mammograms. We have used 168 images that were carefully selected by a radiologist and their abnormalities were also confirmed by biopsy. These images included asymmetric lesions, architectural distortion, normal tissue and mass lesion where in case of mass lesion they included circumscribed benign, ill-defined and spiculated malignant masses. At first, by using wavelet transform and piecewise linear coefficient mapping, image enhancement were done. Secondly detection of lesions was done by fractal method as a ROI. Since in investigation of breast cancer, it is important that fibroglandular tissues in both breasts be symmetric and for each asymmetric density, evaluation for malignancy is necessary, we define new fractal features based on extracting asymmetric information from lesions. The fractal features were evaluated on 5 data sets using SVM classifier which enabled to achieve high accuracy in classification of mammograms and diagnostic results. We have also investigated the performance of image enhancement in classification of each data set which shows different effects of enhancement on different lesion types.

Słowa kluczowe

EN

fractal feature; asymmetric feature; abnormal lesion; classification; wavelet; image enhancement

PL

wymiar fraktalny; cechy asymetrii; falka; poprawa jakości obrazu

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2016
• Tom: Vol. 36, no. 1
• Strony: 56--65
• Opis fizyczny: Bibliogr. 21 poz., rys., tab., wykr.

Twórcy

autor

Beheshti S. M. A.

• Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Sayyad-e-Shirazi, Islamshahr, Tehran, Iran

autor

Noubari H. A.

• Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada

autor

Fatemizadeh E.

• Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran

autor

Khalili M.

• Shahid Beheshti University of Medical Sciences, Tehran, Iran

Bibliografia

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• [16] Beheshti SMA, AhmadiNoubari H, Fatemizadeh E, Rezaee M, Khalili M. Mammograms enhancement using wavelet transform and piecewise linear and nonlinear coefficient mapping. 2014 IEEE Middle East Conference on Biomedical Engineering (MECBME). 2014. pp. 107–10.
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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.