Abstract
Efficient and reliable extraction of coronary artery centerline from computed tomography angiography data is a prerequisite for a variety of medical imaging applications. Many authors have combined minimum-cost path algorithms and vesselness measures to extract coronary centerlines. We propose a modular decomposition of this extraction process, in order to facilitate the implementation and comparison of different minimum-cost path strategies allowing users (radiologists and developers) to focus on subsequent image analysis tasks. Evaluation results show a good overlap (> 84%), and small distances with regard to reference centerlines (on average, not larger than the voxel size) in multi-vendor datasets, for two combinations of algorithms that follow this framework. Therefore, it can serve as a starting point to subsequent image analysis stages that require coronary centerlines.
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Correa-Agudelo, E., Flórez-Valencia, L., Orkisz, M., Mouton, C., Dávila Serrano, E.E., Hernández Hoyos, M. (2014). A Modular Workflow Architecture for Coronary Centerline Extraction in Computed Tomography Angiography Data. In: Chmielewski, L.J., Kozera, R., Shin, BS., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671. Springer, Cham. https://doi.org/10.1007/978-3-319-11331-9_19
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DOI: https://doi.org/10.1007/978-3-319-11331-9_19
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