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Segmentation and Landmark Localization Based on Multiple Atlases

Orcun Goksel, Tobias Gass, Gabor Székely
Proceedings of the VISCERAL Challenge at ISBI
May 2014


In this work, we present multi-atlas based techniques for both segmentation and landmark detection. We focus on modality and anatomy independent techniques to be applied to a wide range of input images, in contrast to methods customized to a specific anatomy or image modality. For segmentation, we use label propagation from several atlases to a target image via aMarkov random field (MRF) based registrationmethod, followed by label fusion by majority voting weighted by local cross-correlations. For landmark localization, we use a consensus based fusion of location estimates from several atlases identified by a template-matching approach. Results in IEEE ISBI 2014 VISCERAL challenge as well as VISCERAL Anatomy1 challenge are presented herein.

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  author = {Orcun Goksel and Tobias Gass and Gabor Székely},
  title = {Segmentation and Landmark Localization Based on Multiple Atlases},
  booktitle = {Proceedings of the VISCERAL Challenge at ISBI},
  year = {2014},
  month = {May},
  pages = {37-43},
  editor = {Orcun Goksel},
  series = {CEUR Workshop Proceedings},
  keywords = {}