Random Walks with Shape Prior for Cochlea Segmentation in Ex-vivo MicroCT

  • Authors
  • Ruiz, E.; Kjer, H.M.; Piella, G.; Ceresa, M.; Gonzalez-Ballester, M.A.
  • UPF authors
  • PIELLA FENOY, GEMA; GONZALEZ BALLESTER, MIGUEL ANGEL;
  • Type
  • Scholarly articles
  • Journal títle
  • International Journal of Computer Assisted Radiology and Surgery
  • Publication year
  • 2016
  • Volume
  • 11
  • Number
  • 9
  • Pages
  • 1647-1659
  • ISSN
  • 1861-6410
  • Publication State
  • Published
  • Abstract
  • Purpose: Cochlear implantation is a safe and effective surgical procedure to restore hearing in deaf patients. However, the level of restoration achieved may vary due to differences in anatomy, implant type and surgical access. In order to reduce the variability of the surgical outcomes, we previously proposed the use of a high-resolution model built from οCT images and then adapted to patient-specific clinical CT scans. As the accuracy of the model is dependent on the precision of the original segmentation, it is extremely important to have accurate οCT segmentation algorithms. Methods: We propose a new framework for cochlea segmentation in ex vivo οCT images using random walks where a distance-based shape prior is combined with a region term estimated by a Gaussian mixture model. The prior is also weighted by a confidence map to adjust its influence according to the strength of the image contour. Random walks is performed iteratively, and the prior mask is aligned in every iteration. Results: We tested the proposed approach in ten οCT data sets and compared it with other random walks-based segmentation techniques such as guided random walks (Eslami et al. in Med Image Anal 17(2):236‿253, 2013) and constrained random walks (Li et al. in Advances in image and video technology. Springer, Berlin, pp 215‿226, 2012). Our approach demonstrated higher accuracy results due to the probability density model constituted by the region term and shape prior information weighed by a confidence map. Conclusion: The weighted combination of the distance-based shape prior with a region term into random walks provides accurate segmentations of the cochlea. The experiments suggest that the proposed approach is robust for cochlea segmentation.
  • Complete citation
  • Ruiz, E.; Kjer, H.M.; Piella, G.; Ceresa, M.; Gonzalez-Ballester, M.A.. Random Walks with Shape Prior for Cochlea Segmentation in Ex-vivo MicroCT . International Journal of Computer Assisted Radiology and Surgery 2016; 11(9): 1647-1659.
Bibliometric indicators
  • 2 times cited Scopus
  • 1 times cited WOS
  • Índex Scimago de 0.565(2016)