Localization of the Lumbar Discs Using Machine Learning and Exact Probabilistic Inference


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Oktay A. B. , Akgul Y. S.

14th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Toronto, Canada, 18 - 22 September 2011, vol.6893, pp.158-165 identifier identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 6893
  • Doi Number: 10.1007/978-3-642-23626-6_20
  • City: Toronto
  • Country: Canada
  • Page Numbers: pp.158-165
  • Keywords: lumbar disc detection, graphical models, exact probabilistic inference, object detection

Abstract

We propose a novel fully automatic approach to localize the lumbar intervertebral discs in MR images with PHOG based SVM and a probabilistic graphical model. At the local level, our method assigns a score to each pixel in target image that indicates whether it is a disc center or not. At the global level, we define a chain-like graphical model that represents the lumbar intervertebral discs and we use an exact inference algorithm to localize the discs. Our main contributions are the employment of the SVM with the PHOG based descriptor which is robust against variations of the discs and a graphical model that reflects the linear nature of the vertebral column. Our inference algorithm runs in polynomial time and produces globally optimal results. The developed system is validated on a real spine MR,I dataset and the final localization results are favorable compared to the results reported in the literature.