| Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey | |
| Huang, Qinghua1,2,3; Zhang, Fan4; Li, Xuelong5; Huang, QH (reprint author), Northwestern Polytech Univ, Sch Mech Engn, Xian 710072, Shaanxi, Peoples R China. | |
| 作者部门 | 光学影像学习与分析中心 |
| 2018 | |
| 发表期刊 | BIOMED RESEARCH INTERNATIONAL
 |
| ISSN | 2314-6133 |
| 产权排序 | 5 |
| 摘要 | The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizingmachine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system. |
| 文章类型 | Review |
| 学科领域 | Biotechnology & Applied Microbiology |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| DOI | 10.1155/2018/5137904 |
| 收录类别 | SCI |
| 关键词[WOS] | CONVOLUTIONAL NEURAL-NETWORKS ; POWER DOPPLER ULTRASOUND ; BREAST ULTRASOUND ; IMAGE CLASSIFICATION ; CAROTID ULTRASOUND ; TRANSFORM FEATURES ; TEXTURE ; LESIONS ; TUMORS ; MASSES |
| 语种 | 英语 |
| WOS研究方向 | Biotechnology & Applied Microbiology ; Research & Experimental Medicine |
| WOS类目 | Biotechnology & Applied Microbiology ; Medicine, Research & Experimental |
| WOS记录号 | WOS:000426555700001 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/29989 |
| 专题 | 光谱成像技术研究室 |
| 通讯作者 | Huang, QH (reprint author), Northwestern Polytech Univ, Sch Mech Engn, Xian 710072, Shaanxi, Peoples R China. |
| 作者单位 | 1.Northwestern Polytech Univ, Sch Mech Engn, Xian 710072, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian 710072, Shaanxi, Peoples R China 3.Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R China 4.South China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China 5.Chinese Acad Sci, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Qinghua,Zhang, Fan,Li, Xuelong,et al. Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey[J]. BIOMED RESEARCH INTERNATIONAL,2018. |
| APA | Huang, Qinghua,Zhang, Fan,Li, Xuelong,&Huang, QH .(2018).Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey.BIOMED RESEARCH INTERNATIONAL. |
| MLA | Huang, Qinghua,et al."Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey".BIOMED RESEARCH INTERNATIONAL (2018). |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Machine Learning in （1517KB） | 期刊论文 | 作者接受稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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