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Automated Detection of Left Ventricle in 4D MR Images: Experience from a Large Study

  • Xiang Lin
  • Brett R. Cowan
  • Alistair A. Young
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

We present a fully automated method to estimate the location and orientation of the left ventricle (LV) in four-dimensional (4D) cardiac magnetic resonance (CMR) images without any user input. The method is based on low-level image processing techniques incorporating anatomical knowledge and is able to provide rapid, robust feedback for automated scan planning or further processing. The method relies on a novel combination of temporal Fourier analysis of image cines with simple contour detection to achieve a fast localization of the heart. Quantitative validation was performed using 4D CMR datasets from 330 patients (54024 images) with a range of cardiac and vascular disease by comparing manual location with the automatic results. The method failed on one case, and showed average bias and precision of under 5mm in apical, mid-ventricular and basal slices in the remaining 329. The errors in automatic orientation were similar to the errors in scan planning as performed by experienced technicians.

Keywords

Cardiac Magnetic Resonance Orientation Error Cardiac Magnetic Resonance Examination Middle Slice SPAMM Image 
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 2006

Authors and Affiliations

  • Xiang Lin
    • 1
  • Brett R. Cowan
    • 2
  • Alistair A. Young
    • 1
  1. 1.Bioengineering InstituteUniversity of AucklandNew Zealand
  2. 2.Center for Advanced MRIUniversity of AucklandNew Zealand

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