A Fast Region-Based Active Contour Model for Boundary Detection of Echocardiographic Images.

This paper presents the boundary detection of atrium and ventricle in echocardiographic images. In case of mitral regurgitation, atrium and ventricle may get dilated. To examine this, doctors draw the boundary manually. Here the aim of this paper is to evolve the automatic boundary detection for car...

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Publicado en:Journal of Digital Imaging Vol. 25; no. 2; pp. 271 - 279
Autores principales: Saini, Kalpana, Dewal, M., Rohit, Manojkumar
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Apr2012
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2012
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      pub: Springer Nature
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        atl: A Fast Region-Based Active Contour Model for Boundary Detection of Echocardiographic Images.
      aug:
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          Saini, Kalpana
          Dewal, M.
          Rohit, Manojkumar
        affil: Department of Electrical Engg, IIT Roorkee, Roorkee India
      sug:
        subj:
          Echocardiography
          Heart Atrium Radiography
          Heart Ventricle Radiography
          Mitral Valve Insufficiency Diagnosis
          Radiographic Image Interpretation, Computer-Assisted
          Automation
          Algorithms
          Human
          Evaluation Research
      ab: This paper presents the boundary detection of atrium and ventricle in echocardiographic images. In case of mitral regurgitation, atrium and ventricle may get dilated. To examine this, doctors draw the boundary manually. Here the aim of this paper is to evolve the automatic boundary detection for carrying out segmentation of echocardiography images. Active contour method is selected for this purpose. There is an enhancement of Chan-Vese paper on active contours without edges. Our algorithm is based on Chan-Vese paper active contours without edges, but it is much faster than Chan-Vese model. Here we have developed a method by which it is possible to detect much faster the echocardiographic boundaries. The method is based on the region information of an image. The region-based force provides a global segmentation with variational flow robust to noise. Implementation is based on level set theory so it easy to deal with topological changes. In this paper, Newton-Raphson method is used which makes possible the fast boundary detection.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
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        Journal Article
      ougenre: Article
    language: English
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