COMPARISON BETWEEN AUTOMATIC AND SEMIAUTOMATIC THRESHOLDING METHOD FOR MAMMOGRAPHIC DENSITY CLASSIFICATION

SHOFWATUL ‘UYUN, DKK (2014) COMPARISON BETWEEN AUTOMATIC AND SEMIAUTOMATIC THRESHOLDING METHOD FOR MAMMOGRAPHIC DENSITY CLASSIFICATION. Advanced Materials Research, Vol. 8. pp. 672-675.

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Abstract

Mammographic density is a novel independent risk factor of breast cancer that reflects the amount of fibroglandular tissue. Breast Imaging Reporting and Data System (BIRADS) density is one of the mammographic density classification schemes which are most widely used by radiologists. Initially, the method used for assessing mammographic density was subjective and qualitative. Recently however, the measurement of mammographic density is more objective and quantitative. In this paper, we propose an alternative model of breast cancer risk factor assessment based on a quantitative approach of density mammogram. This model consists of pre-processing, breast area counting, fibroglandular tissue area counting that uses maximum entropy and multilevel thresholds, and finally breast density counting to determine the risk classification of breast cancer. The proposed model has been tested on a private database from Oncology Clinic Kotabaru, Yogyakarta, Indonesia consisting of 30 mammograms and has been analyzed by some radiologists using the semiautomatic threshold. The result shows that percentage of mammographic density counted by maximum entropy threshold method has the accuracy, sensitivity and specificity of about 67%, 50% and 75% respectively compared to the semiautomatic thresholding method. On the other hand, the accuracy, sensitivity and specificity resulted from using multilevel threshold is about 93%, 87% and 95% respectively. The obtained results suggest that multilevel threshold is perfectly suited for getting quantitative measurement of mammographic density as one of the strongest risk factors for breast cancer.

Item Type: Article
Uncontrolled Keywords: mammographic density classification, breast cancer risk, automatic threshold, semi automatic threshold
Subjects: Sains
Divisions: Artikel (Terbitan Luar UIN)
Depositing User: Sugeng Hariyanto, SIP (sugeng.hariyanto@uin-suka.ac.id)
Date Deposited: 16 Feb 2016 10:30
Last Modified: 16 Feb 2016 10:30
URI: http://digilib.uin-suka.ac.id/id/eprint/19346

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