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Automatic Computer-Aided Detection of Mass using Digital Mammography with Dense Breast
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유방암 조기발견을 위한 치밀 유방 영상에서의 종양 자동 검출 기법 연구

논문 기본 정보

Type
Proceeding
Author
Ji Eun Oh (국립암센터) Yoon Woong Bae (국립암센터) Kwang Gi Kim (국립암센터) Eun Young Chae (서울아산병원) Hak Hee Kim (서울아산병원) Soo Yeul Lee (전자통신연구원)
Journal
The Institute of Electronics and Information Engineers 대한전자공학회 학술대회 2016 IEIE SUMMER CONFERENCE
Published
2016.6
Pages
1,484 - 1,487 (4page)

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Automatic Computer-Aided Detection of Mass using Digital Mammography with Dense Breast
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Research history (2)

2016

Automatic Computer-Aided Detection of Mass using Digital Mammography with Dense Breast
Ji Eun Oh ,  Yoon Woong Bae ,  Kwang Gi Kim and others 3 대한전자공학회 학술대회 2016.06 Proceeding

2015

Automatic Computer-Aided Detection of Microcalcification Cluster using Digital Mammography
Ji Eun Oh ,  Yoon Woong Bae ,  Kwang Gi Kim and others 3 대한전자공학회 학술대회 2015.06 Proceeding
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Abstract· Keywords

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Early detection of breast cancer is crucial to improving the breast cancer prognosis and reducing the mortality rates. Mass in digital mammography are a major sign of breast cancer in early stage. In this study, we proposed an automatic detection method of mass in digital mammography. First, we extracted the breast region and then the high intensity artifacts, such as labels or scanning artifacts, were removed. Second, we enhanced the contrast to emphasize mass with low density in dense breast regions. We detected the mass candidates by using DoG(Difference of Gaussian) and LET(Local Entropy Thresholding) algorithms. Candidates of mass and false positives of them are then reduced by using knowledge based rules. The proposed method achieves a sensitivity of 89.47% at 2.56 false positive per image. In the early diagnosis of breast cancer, the proposed algorithm can be useful for the mass detection.

Contents

Abstract
Ⅰ. 서론
Ⅱ. 본론
Ⅲ. 결과
Ⅳ. 결론 및 향후 연구 방향
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