Breast Cancer Diagnosis Based on Frequency Converters and Extraction of Effective Features
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_EAR-1-2_004
تاریخ نمایه سازی: 20 آذر 1403
Abstract:
Breast cancer is the most common type of cancer among women. Early diagnosis of this disease and its treatment can significantly reduce the death rate from this cancer. The separation of benign and malignant masses in mammography images is one of the important things in the timely detection of breast cancer, which in some cases, due to the density and natural structure of the breast, deep and hidden disorders, make the diagnosis difficult for radiologists. In this study, frequency transformations and Naive Bayes classification have been used with the aim of extracting effective features in mammography images. The aim of the presented method is to increase the accuracy of diagnosis between malignant and benign tumors in mammography images. The results obtained from the implementation of the proposed method on the MIAS database show that the proposed method has been able to improve the accuracy of diagnosing this disease on normal and abnormal images by ۹۱%, Precision by ۹۸%, Recall by ۹۸۷%, and F-measure by ۹۰%.
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Authors
Farnaz Hoseini
Assistant Professor, Department of Computer Engineering, Technical and Vocational University (TVU), Tehran, Iran.
Hamed Sepehrzadeh
Assistant Professor, Department of Computer Engineering, Technical and Vocational University (TVU), Tehran, Iran.
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