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Robustness Analysis of Coronary Arteries Segmentation

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Smart Modeling for Engineering Systems (GCM50 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 133))

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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.

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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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Authors and Affiliations

  1. Marchuk Institute of Numerical Mathematics of the RAS, 8, Gubkina ul, Moscow, 119991, Russian Federation

    Roman Pryamonosov & Alexander Danilov

  2. Moscow Institute of Physics and Technology (MIPT), 9 Institutskiy per, Dolgoprudny, Moscow Region, 141701, Russian Federation

    Roman Pryamonosov & Alexander Danilov

  3. Sechenov University, 4, Bolshaya Pirogovskaya ul, Moscow, 119991, Russian Federation

    Roman Pryamonosov & Alexander Danilov

Authors
  1. Roman Pryamonosov
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  2. Alexander Danilov
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Corresponding author

Correspondence to Roman Pryamonosov .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Numerical Mathematics, Moscow Institute of Physics and Technology, Dolgoprudny, The Moscow Area, Russia

    Igor B. Petrov

  2. Department of Applied Computational Geophysics, Moscow Institute of Physics and Technology, Dolgoprudny, The Moscow Area, Russia

    Alena V. Favorskaya

  3. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  4. Department of Computational Physics, Moscow Institute of Physics and Technology, Dolgoprudny, The Moscow Area, Russia

    Sergey S. Simakov

  5. Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology, Sydney, NSW, Australia

    Lakhmi C. Jain

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Pryamonosov, R., Danilov, A. (2019). Robustness Analysis of Coronary Arteries Segmentation. In: Petrov, I., Favorskaya, A., Favorskaya, M., Simakov, S., Jain, L. (eds) Smart Modeling for Engineering Systems. GCM50 2018. Smart Innovation, Systems and Technologies, vol 133. Springer, Cham. https://doi.org/10.1007/978-3-030-06228-6_26

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