Skip to main content
Top

2019 | OriginalPaper | Chapter

Context Aware 3D Fully Convolutional Networks for Coronary Artery Segmentation

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Cardiovascular disease caused by coronary artery disease (CAD) is one of the most common causes of death worldwide. Coronary artery segmentation has attracted increasing attention since it is useful for better visualization and diagnosis. Conventional lumen segmentation methods basically describe vessels by a rough tubular model, thus presenting inferiority on abnormal vascular structures and failing to distinguish exact coronary arteries from vessel-like structures. In this paper, we propose a context aware 3D fully convolutional network (FCN) for vessel enhancement and segmentation in coronary computed tomography angiography (CTA) volumes. Combining the superior capacity of CNN in extracting discriminative features and satisfactory suppression of vessel-like structures by spatial prior knowledge embedded, the proposed approach significantly outperforms conventional Hessian vesselness based approach on a dataset of 50 coronary CTA volumes.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Roger, V.L., et al.: Heart disease and stroke statistics-2012 update: a report from the american heart association. Circulation 125(1), e2–e220 (2012) CrossRef Roger, V.L., et al.: Heart disease and stroke statistics-2012 update: a report from the american heart association. Circulation 125(1), e2–e220 (2012) CrossRef
3.
go back to reference Lesage, D., Angelini, E.D., Bloch, I., Funka-Lea, G.: A review of 3D vessel lumen segmentation techniques: models, features and extraction schemes. Med. Image Anal. 13(6), 819–845 (2009) CrossRef Lesage, D., Angelini, E.D., Bloch, I., Funka-Lea, G.: A review of 3D vessel lumen segmentation techniques: models, features and extraction schemes. Med. Image Anal. 13(6), 819–845 (2009) CrossRef
4.
go back to reference Zheng, Y., Loziczonek, M., Georgescu, B., Zhou, S.K., Vega-Higuera, F., Comaniciu, D.: Machine learning based vesselness measurement for coronary artery segmentation in cardiac CT volumes. In: Proceedings of the SPIE 7962, Medical Imaging 2011: Image Processing. p. 79621K (2011) Zheng, Y., Loziczonek, M., Georgescu, B., Zhou, S.K., Vega-Higuera, F., Comaniciu, D.: Machine learning based vesselness measurement for coronary artery segmentation in cardiac CT volumes. In: Proceedings of the SPIE 7962, Medical Imaging 2011: Image Processing. p. 79621K (2011)
5.
go back to reference Chen, F., Li, Y., Tian, T., Cao, F., Liang, J.: Automatic coronary artery lumen segmentation in computed tomography angiography using paired multi-scale 3D CNN. In: Proceedings of the SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, p. 105782R (2018) Chen, F., Li, Y., Tian, T., Cao, F., Liang, J.: Automatic coronary artery lumen segmentation in computed tomography angiography using paired multi-scale 3D CNN. In: Proceedings of the SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, p. 105782R (2018)
6.
go back to reference Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., Brox, T., Ronneberger, O.: 3D U-Net: learning dense volumetric segmentation from sparse annotation. MICCA I, 424–432 (2016) Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., Brox, T., Ronneberger, O.: 3D U-Net: learning dense volumetric segmentation from sparse annotation. MICCA I, 424–432 (2016)
7.
go back to reference Milletari, F., Navab, N., Ahmadi, S.A.: V-Net: Fully convolutional neural networks for volumetric medical image segmentation. In: Fourth International Conference on 3D Vision (3DV), pp. 565–571. IEEE (2016) Milletari, F., Navab, N., Ahmadi, S.A.: V-Net: Fully convolutional neural networks for volumetric medical image segmentation. In: Fourth International Conference on 3D Vision (3DV), pp. 565–571. IEEE (2016)
8.
go back to reference Zhou, S.K.: Discriminative anatomy detection: classification vs regression. Pattern Recognit. Lett. 43, 25–38 (2014) CrossRef Zhou, S.K.: Discriminative anatomy detection: classification vs regression. Pattern Recognit. Lett. 43, 25–38 (2014) CrossRef
9.
go back to reference He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770–778 (2016) He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770–778 (2016)
10.
go back to reference Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollar, P.: Focal loss for dense object detection. In: ICCV, pp. 2980–2988 (2017) Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollar, P.: Focal loss for dense object detection. In: ICCV, pp. 2980–2988 (2017)
11.
go back to reference Yang, X., Bian, C., Yu, L., Ni, D., Heng, P.A.: Hybrid loss guided convolutional networks for whole heart parsing. In: International Workshop on Statistical Atlases and Computational Models of the Heart, pp. 215–223 (2017) Yang, X., Bian, C., Yu, L., Ni, D., Heng, P.A.: Hybrid loss guided convolutional networks for whole heart parsing. In: International Workshop on Statistical Atlases and Computational Models of the Heart, pp. 215–223 (2017)
Metadata
Title
Context Aware 3D Fully Convolutional Networks for Coronary Artery Segmentation
Authors
Yongjie Duan
Jianjiang Feng
Jiwen Lu
Jie Zhou
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-12029-0_10

Premium Partner