Abstract
One of the independently risk factors of breast cancer is mammographic density reflecting the composition of the fibroglandular tissue in breast area. Tumor in the mammogram is precisely complicated to detect as it is covered by the density (the masking effect). The determination of mammographic density may be implemented by calculating percentage of mammographic density (quantitative and objective approaches). Thereby, the use of a proper thresholding algorithm is highly required in order to obtain the fibroglandular tissue area and breast area. The mammograms used in the research were derived from Oncology Clinic, Yogyakarta that had been verified by Radiologists using semi-automatic thresholding. This research was aimed to compare the performance of the thresholding algorithm using three parameters, namely: PME, RAE and MHD. Zack Algorithm had the best performance to obtain the breast area with PME, RAE and MHD of about 0.33%, 0.71% and 0.01 respectively. Meanwhile, there were two algorithms having good performance to obtain the fibroglandular tissue area, i.e. multilevel thresholding and maximum entropy with the value for PME (13.34%; 11:27%), RAE (53.34%; 51.26%) and MHD (1:47; 33.92) respectively. The obtained results suggest that zack algorithm is perfectly suited for getting breast area than multilevel thresholding and maximum entropy for getting fibroglandular tissue. It is one of the components to determine risk factors of breast cancer based on percentage of breast density. Keywords: Thresholding Algorithm; Breast Area; fibroglandular Area
Highlights
One of the preventive measures to decrease the number of breast cancer patients is by having routine screenings
The use of proper thresholding method will be able to separate discriminate the fat tissue in the breast area and its background and/or to separate the fibroglandular tissue and fat tissue based on the threshold value obtained
The final process in this research is the analysis to determine the performance of each automated thresholding algorithm that is used to obtain the breast area and the fibroglandular tissue area
Summary
One of the preventive measures to decrease the number of breast cancer patients is by having routine screenings. To obtain areas, (fibroglandular tissue area and fat tissue in the breast area), it is necessary to conduct segmentation process automatically by employing thresholding method. The use of proper thresholding method will be able to separate discriminate the fat tissue in the breast area and its background and/or to separate the fibroglandular tissue and fat tissue based on the threshold value obtained. After obtaining these two areas, the ratio value can be calculated, between the fibroglandular tissue and breast area, indicating the risk factors of breast cancer. The result of threshold value can be performed either automatically or semi-automatically
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