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  5. Breast Cancer Detection and Classification on Mammogram Images Using Morphological Approach
 
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Breast Cancer Detection and Classification on Mammogram Images Using Morphological Approach

Journal
IICETA 2022 - 5th International Conference on Engineering Technology and its Applications
Date Issued
2022-01-01
Author(s)
Wan Azani Wan Mustafa
Universiti Malaysia Perlis
Azmi A.A.
Mohd Aminudin Jamlos
Universiti Malaysia Perlis
Alquran H.
Wan Khairunizam Wan Ahmad
Universiti Malaysia Perlis
Ismail S.
Alkhayyat A.
Haron J.
DOI
10.1109/IICETA54559.2022.9888432
Abstract
Breast cancer is one of the most common cancers affecting women worldwide. Mammography is the most well-known and effective method to detect early signs of breast cancer. The purpose of this paper is to detect breast cancer on the mammogram image to classify the disease through morphological techniques. Using conventional methods makes radiology difficult to detect cancer found in the patient's breast. This proposal can be divided into several elements, which are input database, image preprocessing, image segmentation, morphological analysis, and object recognition. First, image preprocessing will be done using the Weiner and Median filters. Second, the thresholding method for image segmentation will be performed, and lastly, morphology will remove imperfections introduced during the image segmentation process. Finally, the image is classified into two classes: normal and cancerous images. A median filter and 0.95 thresholding achieve an accuracy of 93.71%, a sensitivity of 94.36%, and a specificity of 82.53% for the cancerous images.
Subjects
  • breast | cancer | det...

File(s)
Research repository notification.pdf (4.4 MB)
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