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Towards automatic quantification of the epicardial fat in non-contrasted CT images

Author

Listed:
  • Jorge Barbosa
  • Bruno Figueiredo
  • Nuno Bettencourt
  • João Tavares

Abstract

In this work, we present a technique to semi-automatically quantify the epicardial fat in non-contrasted computed tomography (CT) images. The epicardial fat is very close to the pericardial fat, being separated only by the pericardium that appears in the image as a very thin line, which is hard to detect. Therefore, an algorithm that uses the anatomy of the heart was developed to detect the pericardium line via control points of the line. From the points detected an interpolation was applied based on the cubic interpolation, which was also improved to avoid incorrect interpolation that occurs when the two variables are non-monotonic. The method is validated by using a set of 40 CT images of the heart of 40 human subjects. In 62.5% of the cases only minimal user intervention was required and the results compared favourably with the results obtained by the manual process.

Suggested Citation

  • Jorge Barbosa & Bruno Figueiredo & Nuno Bettencourt & João Tavares, 2011. "Towards automatic quantification of the epicardial fat in non-contrasted CT images," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 14(10), pages 905-914.
    • Handle: RePEc:taf:gcmbxx:v:14:y:2011:i:10:p:905-914
    DOI: 10.1080/10255842.2010.499871
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    References listed on IDEAS

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    1. Zhen Ma & João Manuel R.S. Tavares & Renato Natal Jorge & T. Mascarenhas, 2010. "A review of algorithms for medical image segmentation and their applications to the female pelvic cavity," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 13(2), pages 235-246.
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