期刊
ULTRASONICS
卷 76, 期 -, 页码 70-77出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ultras.2016.12.017
关键词
Breast cancer; Screening ultrasound; Computer-aided diagnosis
资金
- Ministry of Science and Technology [MOST 103-2221-E-002-170-MY3]
- Ministry of Economic Affairs [102-EC-17-A-19-51-164]
- Department of Health [DOH102-TD-C111-001]
- Ministry of Education of Taiwan [AE-00-00-06]
- National Research Foundation of Korea (NRF) - Korea government (MSIP) [2012R1A2A1A01010846]
- National Research Foundation of Korea [2012R1A2A1A01010846] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Screening ultrasound (US) is increasingly used as a supplement to mammography in women with dense breasts, and more than 80% of cancers detected by US alone are 1 cm or smaller. An adaptive computer aided diagnosis (CAD) system based on tumor size was proposed to classify breast tumors detected at screening US images using quantitative morphological and textural features. In the present study, a database containing 156 tumors (78 benign and 78 malignant) was separated into two subsets of different tumor sizes (< 1 cm and >= 1 cm) to explore the improvement in the performance of the CAD system. After adaptation, the accuracies, sensitivities, specificities and Az values of the CAD for the entire database increased from 73.1% (114/156), 73.1% (57/78), 73.1% (57/78), and 0.790 to 81.4% (127/156), 83.3% (65/78), 79.5% (62/78), and 0.852, respectively. In the data subset of tumors larger than 1 cm, the performance improved from 66.2% (51/77), 68.3% (28/41), 63.9% (23/36), and 0.703 to 81.8%(63/77),85.4% (35/41), 77.8% (28/36), and 0.855, respectively. The proposed CAD system can be helpful to classify breast tumors detected at screening US. (C) 2016 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据