Abstract
A novel approach to segment cardiac magnetic resonance (CMR) images is presented in order to overcome some challenges such as problems with papillary muscles and the non homogeneities of the cavity due to blood flow. It consists in filtering short axis CMR images, using connected operators (area-open and area-close filters) to homogenize the cavity, prior to the segmentation which is performed using GVF-Snake algorithm in two steps. Validation was performed on thirty-nine slices by comparing resulting segmentation to the manual contours traced by an expert. This comparison showed good results with an overall average similarity area of 90.7% and an average distance between the two contours of 0.6 pixel.
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El Berbari, R. et al. (2007). Automated Segmentation of the Left Ventricle Including Papillary Muscles in Cardiac Magnetic Resonance Images. In: Sachse, F.B., Seemann, G. (eds) Functional Imaging and Modeling of the Heart. FIMH 2007. Lecture Notes in Computer Science, vol 4466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72907-5_46
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DOI: https://doi.org/10.1007/978-3-540-72907-5_46
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