| A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images | |
| Luo, Yaozhong1; Liu, Longzhong2; Huang, Qinghua1,3; Li, Xuelong4; Huang, QH (reprint author), South China Univ Technol, Sch Elect & Informat Engn, Guangzhou, Guangdong, Peoples R China. | |
| 作者部门 | 光学影像学习与分析中心 |
| 2017 | |
| 发表期刊 | BIOMED RESEARCH INTERNATIONAL
 |
| ISSN | 2314-6133 |
| 产权排序 | 4 |
| 摘要 | Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB) segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI) on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO) algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%), the second highest TPVF (85.34%), and the second lowest FPVF (4.48%). |
| 文章类型 | Article |
| 学科领域 | Biotechnology & Applied Microbiology |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| DOI | 10.1155/2017/9157341 |
| 收录类别 | SCI |
| 关键词[WOS] | COMPUTER-AIDED DIAGNOSIS ; GEODESIC ACTIVE CONTOURS ; GRAPH-BASED SEGMENTATION ; SOLID BREAST NODULES ; B-MODE IMAGES ; LEVEL-SET ; NEURAL-NETWORKS ; 2-D SONOGRAPHY ; TUMOR ; LESIONS |
| 语种 | 英语 |
| WOS研究方向 | Biotechnology & Applied Microbiology ; Research & Experimental Medicine |
| 项目资助者 | National Natural Science Foundation of China(61372007 ; Guangzhou Key Lab of Body Data Science(201605030011) ; Guangdong Provincial Science and Technology Program-International Collaborative Projects(2014A050503020) ; 61571193) |
| WOS类目 | Biotechnology & Applied Microbiology ; Medicine, Research & Experimental |
| WOS记录号 | WOS:000400407100001 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/28900 |
| 专题 | 光谱成像技术研究室 |
| 通讯作者 | Huang, QH (reprint author), South China Univ Technol, Sch Elect & Informat Engn, Guangzhou, Guangdong, Peoples R China. |
| 作者单位 | 1.South China Univ Technol, Sch Elect & Informat Engn, Guangzhou, Guangdong, Peoples R China 2.Sun Yat Sen Univ, Dept Ultrasound, Ctr Canc, State Key Lab Oncol South China,Collaborat Innova, Guangzhou, Guangdong, Peoples R China 3.Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R China 4.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Yaozhong,Liu, Longzhong,Huang, Qinghua,et al. A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images[J]. BIOMED RESEARCH INTERNATIONAL,2017. |
| APA | Luo, Yaozhong,Liu, Longzhong,Huang, Qinghua,Li, Xuelong,&Huang, QH .(2017).A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images.BIOMED RESEARCH INTERNATIONAL. |
| MLA | Luo, Yaozhong,et al."A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images".BIOMED RESEARCH INTERNATIONAL (2017). |
| 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 | ||
| A Novel Segmentation（8232KB） | 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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