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Robustness Analysis of Coronary Arteries Segmentation

  • Roman PryamonosovEmail author
  • Alexander Danilov
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 133)

Abstract

Segmentation of medical scans is the first and fundamental stage of numerical modeling of the human cardiovascular system. In this chapter, we analyze the results of coronary arteries segmentation using our approach for ten contrast-enhanced Computer Tomography Angiography datasets with different image quality and contrast phases. The segmentation is also affected by the patient anatomy, the shape and the scope of images. Our results show that the contrast phase timing is crucial for successful automatic segmentation. These factors form restrictions on the input data for automatic segmentation algorithms. Nevertheless, user guidance such as manual seeding and setting of thresholds can be used to significantly improve segmentation results and weaken the input restrictions.

Keywords

Image segmentation Coronary arteries Contrast enhanced Computed tomography Cardiovascular applications Personalized medicine 

Notes

Acknowledgements

The authors acknowledge Kopylov and Gognieva of the Sechenov University and Fuyou of the Shanghai Jiao Tong University for anonymized patient data, and two reviewers for valuable comments and suggestions. This work has been supported by the Russian Science Foundation (RSF), grant 14-31-00024.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Marchuk Institute of Numerical Mathematics of the RASMoscowRussian Federation
  2. 2.Moscow Institute of Physics and Technology (MIPT)Dolgoprudny, Moscow RegionRussian Federation
  3. 3.Sechenov UniversityMoscowRussian Federation

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