Paper
19 November 2013 Comparative study of variational and level set approaches for shape extraction in cardiac CT images
Author Affiliations +
Proceedings Volume 8922, IX International Seminar on Medical Information Processing and Analysis; 89220Y (2013) https://doi.org/10.1117/12.2035502
Event: IX International Seminar on Medical Information Processing and Analysis, 2013, Mexico City, Mexico
Abstract
Variational approaches based on level set representation have become some of the most important methodologies used to handle the segmentation tasks of biological structures in medical images. Because the segmentation is one of the most challenging processes in medical applications, all the methods fail to achieve perfect results. The major problems are due to noise, poor contrast and high variation of the structure shapes. In this paper, we review the principal level set – based methods that have been designed for image segmentation applications. These approaches include: Geodesic Active Contour, Chan-Vese Functional and Geodesic Active Regions. We also shortly analyze the first method proposed for shape extraction in images by using level set representation. We make a comparative study of the performance obtained for each method applied on cardiac CT images which present strong and very marked differences about the contrast and shape variation. Left ventricle is selected as structure of analysis. Measures of similarity are used to evaluate the performance of the methods.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Barba-J. Leiner, Boris Escalante-Ramírez, and Enrique Vallejo "Comparative study of variational and level set approaches for shape extraction in cardiac CT images", Proc. SPIE 8922, IX International Seminar on Medical Information Processing and Analysis, 89220Y (19 November 2013); https://doi.org/10.1117/12.2035502
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KEYWORDS
Image segmentation

Computed tomography

Medical imaging

Image processing

Visualization

Tomography

Heart

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