A Modular Workflow Architecture for Coronary Centerline Extraction in Computed Tomography Angiography Data
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 mod...
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Published in | Computer Vision and Graphics pp. 155 - 162 |
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Main Authors | , , , , , |
Format | Book Chapter |
Language | English |
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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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AbstractList | 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. |
Author | Hernández Hoyos, Marcela Correa-Agudelo, Esteban Orkisz, Maciej Dávila Serrano, Eduardo E. Mouton, Claire Flórez-Valencia, Leonardo |
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SubjectTerms | centerline extraction computed tomography coronary arteries minimum cost-path algorithms vesselness |
Title | A Modular Workflow Architecture for Coronary Centerline Extraction in Computed Tomography Angiography Data |
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