A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images
文献类型：期刊论文
| 作者 | Luo, Yaozhong1; Liu, Longzhong2; Huang, Qinghua1,3; Li, Xuelong4 |
| 刊名 | biomed research international
 |
| 出版日期 | 2017 |
| ISSN号 | 2314-6133 |
| 产权排序 | 4 |
| 通讯作者 | huang, qh (reprint author), south china univ technol, sch elect & informat engn, guangzhou, guangdong, peoples r china. |
| 英文摘要 | 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%). |
| WOS标题词 | science & technology ; life sciences & biomedicine |
| 学科主题 | biotechnology & applied microbiology ; medicine, research & experimental |
| 类目[WOS] | biotechnology & applied microbiology ; medicine, research & experimental |
| 研究领域[WOS] | biotechnology & applied microbiology ; research & experimental medicine |
| 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 |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000400407100001 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/28900]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 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.(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). |
入库方式： OAI收割
来源：西安光学精密机械研究所
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