지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.9 No.2
- 발행연도
- 2020.4
- 수록면
- 119 - 126 (8page)
- DOI
- 10.5573/IEIESPC.2020.9.2.119
이용수
초록· 키워드
오류제보하기
Breast image analysis is important for the detection and diagnosis of various diseases, but more specifically, breast cancer. The most popular and widely used screening tool is mammography. It gives a better result than other screening tools for breast image analysis. Mammograms are difficult to analyze because of noise, poor quality, artifacts, and the inclusion of pectoral muscle. The technique proposed in this paper has several stages for preprocessing mammograms. First, artifacts and the background are removed by changing the original image into a binary image using Otsu’s thresholding. The medio-lateral view of mammography images has two orientations: left or right. Orientation detection in the next step is important for pectoral muscle removal, which is done using the line segment method. Contrast is enhanced using contrast limited adaptive histogram equalization, and noise is reduced using a median filter. The proposed technique was applied to a publicly available dataset from the Mammographic Image Analysis Society, from which 322 images were analyzed, and performance parameters calculated. After calculations for accuracy, sensitivity, and specificity, the accuracy achieved was 94.62%, sensitivity achieved was 90.21%, and specificity was 97.20%.
목차
Abstract
1. Introduction
2. Related Work
3. The Proposed Scheme
4. Performance Parameters
6. Conclusion and Future Work
5. Results
References
참고문헌 (44)
참고문헌 신청
M. S. Donepudi / 2014 / Breast cancer statistics and markers / Journal of Cancer Research and Therapeutics 10(3):506~511
T. W. Freer / 2001 / Screening Mammography with computer-aided detection:Prospective study of 12860 patients in a community breast center 1 / Radiology 220(3):781~786
E. D. Pisano / 2000 / Image processing algorithms for digital mammography: A pictorial essay 1 / Radiographics 20(5):1479~1491
A. C. Chaabani / 2010 / An Automatic Pre-processing method for Mammographic Images / International Journal of Digital Content Technology and its Applications 4(3):190~201
D. N. Ponraj / 2011 / A survey on the preprocessing techniques of mammogram for the detection of breast cancer / Journal of Emerging Trends in Computing and Informatics Sciences 2(12):656~664
T. W. Freer / 2001 / Screening Mammography with computer-aided detection:Prospective study of 12860 patients in a community breast center 1 / Radiology 220(3):781~786
E. D. Pisano / 2000 / Image processing algorithms for digital mammography: A pictorial essay 1 / Radiographics 20(5):1479~1491
A. C. Chaabani / 2010 / An Automatic Pre-processing method for Mammographic Images / International Journal of Digital Content Technology and its Applications 4(3):190~201
D. N. Ponraj / 2011 / A survey on the preprocessing techniques of mammogram for the detection of breast cancer / Journal of Emerging Trends in Computing and Informatics Sciences 2(12):656~664
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UCI(KEPA) : I410-ECN-0101-2020-569-000541553