A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images.
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 n...
| Publicado en: | BioMed Research International Vol. 2017; pp. 1 - 19 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
4/27/2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122728663&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122728663 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 4/27/2017 vid: 2017 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 122728663 122728663 122728663 10.1155/2017/9157341 122728663 ppf: 1 ppct: 18 formats: fmt: @attributes: type: P tig: atl: A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images. aug: au: Luo, Yaozhong Liu, Longzhong Huang, Qinghua Li, Xuelong affil: School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China sug: subj: Ultrasonography Image Processing, Computer Assisted Methods Algorithms Utilization Image Enhancement Methods Descriptive Statistics Comparative Studies Diagnosis, Computer Assisted ab: 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%). pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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