Automatic detection of calcified coronary plaques in computed tomography data sets

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Abstract

The detection of calcified plaques is an essential step in the assessment of coronary heart diseases. However, manual plaque segmentation is subjected to intra- and inter-observer variability. We present a novel framework for the automatic detection of calcified coronary plaques in Computed Tomography images. In contrast to the state-of-the-art, both the native and the angio data sets are included to gain additional information about each plaque for its detection and subsequent assessment. The framework was successfully tested on 127 patients where 85.5% of the calcified and 96% of the obstructive plaques have been detected. © 2008 Springer-Verlag Berlin Heidelberg.

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Saur, S. C., Alkadhi, H., Desbiolles, L., Székely, G., & Cattin, P. C. (2008). Automatic detection of calcified coronary plaques in computed tomography data sets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5241 LNCS, pp. 170–177). https://doi.org/10.1007/978-3-540-85988-8_21

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