Cochlea segmentation using iterated random walks with shape prior

  • Authors
  • Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Vera, Sergio; Ceresa, Mario; González Ballester, Miguel Ángel
  • UPF authors
  • GONZALEZ BALLESTER, MIGUEL ANGEL;
  • Type
  • Scholarly articles
  • Journal títle
  • Proceedings of SPIE
  • Publication year
  • 2016
  • Volume
  • 9784
  • Pages
  • 0-0
  • ISSN
  • 0277-786X
  • Publication State
  • Published
  • Abstract
  • Cochlear implants can restore hearing to deaf or partially deaf patients. In order to plan the intervention, a model from high resolution µCT images is to be built from accurate cochlea segmentations and then, adapted to a patient-specific model. Thus, a precise segmentation is required to build such a model. We propose a new framework for segmentation of µCT cochlear images using random walks where a region term is combined with a distance shape prior weighted by a confidence map to adjust its influence according to the strength of the image contour. Then, the region term can take advantage of the high contrast between the background and foreground and the distance prior guides the segmentation to the exterior of the cochlea as well as to less contrasted regions inside the cochlea. Finally, a refinement is performed preserving the topology using a topological method and an error control map to prevent boundary leakage. We tested the proposed approach with 10 datasets and compared it with the latest techniques with random walks and priors. The experiments suggest that this method gives promising results for cochlea segmentation
  • Complete citation
  • Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Vera, Sergio; Ceresa, Mario; González Ballester, Miguel Ángel. Cochlea segmentation using iterated random walks with shape prior. Proceedings of SPIE 2016; 9784( ).
Bibliometric indicators
  • 3 times cited Scopus
  • 2 times cited WOS
  • Índex Scimago de 0.24(2016)