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Discriminative Context Modeling Using Auxiliary Markers for LV Landmark Detection from a Single MR Image

  • Xiaoguang Lu
  • Marie-Pierre Jolly
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7746)

Abstract

Cardiac magnetic resonance imaging (MRI) is a key diagnostic tool for non-invasive assessment of the function and structure of the cardiovascular system in clinical practice. Cardiac landmarks provide strong cues to navigate the complex heart anatomy, extract and evaluate morphological and functional features for diagnosis and disease monitoring. A fully automatic method is presented to detect cardiac landmarks from individual images using a learning-based approach to model discriminative context. In addition to the target landmarks, auxiliary markers are taken into consideration to construct context with more discriminative power. The presented approach is evaluated on the STACOM2012 database, containing 100 independent test cases. Automatic landmark detection targets include two mitral valve landmarks in a long axis image, two RV insert landmarks in a short-axis image, and one central axis point in an LV base image.

Keywords

Mitral Valve Cardiac Magnetic Resonance Context Modeling Short Axis Image Landmark Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xiaoguang Lu
    • 1
  • Marie-Pierre Jolly
    • 1
  1. 1.Corporate TechnologySiemens CorporationPrincetonUSA

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