Skip to main content

2015 | OriginalPaper | Buchkapitel

Segmentation of Lumbar Vertebrae Slices from CT Images

verfasst von : Hugo Hutt, Richard Everson, Judith Meakin

Erschienen in: Recent Advances in Computational Methods and Clinical Applications for Spine Imaging

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

We describe a fully automated approach to vertebrae segmentation from CT images which operates on superpixels. The method is based on a conditional random field model incorporating constraints learned from labelled superpixel features. The method is shown to provide consistently accurate segmentations of different vertebrae from a variety of subjects.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Fußnoten
1
Data from the CSI2014 segmentation competition is available from the SpineWeb initiative: http://​spineweb.​digitalimaginggr​oup.​ca.
 
Literatur
1.
Zurück zum Zitat Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Susstrunk, S.: SLIC superpixels compared to State-of-the-Art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012) Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Susstrunk, S.: SLIC superpixels compared to State-of-the-Art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012)
2.
Zurück zum Zitat Blake, A., Kohli, P., Rother, C. (eds.): Markov Random Fields for Vision and Image Processing. The MIT Press, Cambridge (2011)MATH Blake, A., Kohli, P., Rother, C. (eds.): Markov Random Fields for Vision and Image Processing. The MIT Press, Cambridge (2011)MATH
3.
Zurück zum Zitat Boykov, Y., Funka-Lea, G.: Graph cuts and efficient N-D image segmentation. Int. J. Comput. Vis. 70(2), 109–131 (2006)CrossRef Boykov, Y., Funka-Lea, G.: Graph cuts and efficient N-D image segmentation. Int. J. Comput. Vis. 70(2), 109–131 (2006)CrossRef
4.
Zurück zum Zitat Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Trans. Pattern Anal. Mach. Intell. 26(9), 1124–1137 (2004)CrossRef Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Trans. Pattern Anal. Mach. Intell. 26(9), 1124–1137 (2004)CrossRef
6.
Zurück zum Zitat Gerig, G., Jomier, M., Chakos, M.: Valmet: a new validation Tool for assessing and improving 3D object segmentation. In: Medical Image Computing and Computer-Assisted Intervention (MICCAI), vol. 2208, pp. 516–523. Springer (2001) Gerig, G., Jomier, M., Chakos, M.: Valmet: a new validation Tool for assessing and improving 3D object segmentation. In: Medical Image Computing and Computer-Assisted Intervention (MICCAI), vol. 2208, pp. 516–523. Springer (2001)
7.
Zurück zum Zitat Ghosh, S., Alomari, R., Chaudhary, V., Dhillon, G.: Automatic lumbar vertebra segmentation from clinical CT for wedge compression fracture diagnosis. In: SPIE Conference Series, vol. 7963 (2011) Ghosh, S., Alomari, R., Chaudhary, V., Dhillon, G.: Automatic lumbar vertebra segmentation from clinical CT for wedge compression fracture diagnosis. In: SPIE Conference Series, vol. 7963 (2011)
8.
Zurück zum Zitat Huang, J., Jian, F., Wu, H., Li, H.: An improved level set method for vertebra CT image segmentation. BioMed. Eng. OnLine 12(48) (2013) Huang, J., Jian, F., Wu, H., Li, H.: An improved level set method for vertebra CT image segmentation. BioMed. Eng. OnLine 12(48) (2013)
9.
Zurück zum Zitat Hutt, H. W., Everson, R. M., and Meakin, J. R.: Automatic segmentation of vertebrae from MR images. Technical Report, 2014, School of Physics, University of Exeter (2014) Hutt, H. W., Everson, R. M., and Meakin, J. R.: Automatic segmentation of vertebrae from MR images. Technical Report, 2014, School of Physics, University of Exeter (2014)
10.
Zurück zum Zitat Kim, Y., Kim, D.: A fully automatic vertebra segmentation method using 3D deformable fences. Comput. Med. Imaging Graph. 33, 343–352 (2009)CrossRef Kim, Y., Kim, D.: A fully automatic vertebra segmentation method using 3D deformable fences. Comput. Med. Imaging Graph. 33, 343–352 (2009)CrossRef
11.
Zurück zum Zitat Klinder, T., Ostermann, J., Ehm, M., Franz, A., Kneser, R., Lorenz, C.: Automated model-based vertebra detection, identification, and segmentation in CT images. Med. Image Anal. 13(3), 471–482 (2009)CrossRef Klinder, T., Ostermann, J., Ehm, M., Franz, A., Kneser, R., Lorenz, C.: Automated model-based vertebra detection, identification, and segmentation in CT images. Med. Image Anal. 13(3), 471–482 (2009)CrossRef
12.
Zurück zum Zitat Knutsson, H.: Representing Local Structure Using Tensors. In: The 6th Scandinavian Conference on Image Analysis, Oulu, pp. 244–251 (1989) Knutsson, H.: Representing Local Structure Using Tensors. In: The 6th Scandinavian Conference on Image Analysis, Oulu, pp. 244–251 (1989)
13.
Zurück zum Zitat Lim, P.H., Bagci, U., Bai, L.: Introducing willmore flow into level set segmentation of spinal vertebrae. IEEE Trans. Biomed. Eng. 60(1), 115–122 (2013)CrossRef Lim, P.H., Bagci, U., Bai, L.: Introducing willmore flow into level set segmentation of spinal vertebrae. IEEE Trans. Biomed. Eng. 60(1), 115–122 (2013)CrossRef
14.
Zurück zum Zitat Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef
15.
Zurück zum Zitat Torr, P.H.S., Zisserman, A.: MLESAC: a new robust estimator with application to estimating image geometry. Comput. Vis. Image Underst. 78, 138–156 (2000)CrossRef Torr, P.H.S., Zisserman, A.: MLESAC: a new robust estimator with application to estimating image geometry. Comput. Vis. Image Underst. 78, 138–156 (2000)CrossRef
17.
Zurück zum Zitat Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res. 10, 207–244 (2009)MATH Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res. 10, 207–244 (2009)MATH
18.
Zurück zum Zitat Wu, T.-F., Lin, C.-J., Weng, R.C.: Probability estimates for multi-class classification by pair wise coupling. J. Mach. Learn. Res. 5, 975–1005 (2004)MATHMathSciNet Wu, T.-F., Lin, C.-J., Weng, R.C.: Probability estimates for multi-class classification by pair wise coupling. J. Mach. Learn. Res. 5, 975–1005 (2004)MATHMathSciNet
19.
Zurück zum Zitat Yao, J., Burns, J. E., Munoz, H., Summers, R.M.: Detection of Vertebral Body Fractures Based on Cortical Shell Unwrapping. In: Medical Image Computing and Computer-Assisted Intervention (MICCAI), vol. 7512, pp. 509–516. Springer (2012) Yao, J., Burns, J. E., Munoz, H., Summers, R.M.: Detection of Vertebral Body Fractures Based on Cortical Shell Unwrapping. In: Medical Image Computing and Computer-Assisted Intervention (MICCAI), vol. 7512, pp. 509–516. Springer (2012)
Metadaten
Titel
Segmentation of Lumbar Vertebrae Slices from CT Images
verfasst von
Hugo Hutt
Richard Everson
Judith Meakin
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-14148-0_6

Neuer Inhalt