Automated left ventricular segmentation in cardiac MRI

IEEE Trans Biomed Eng. 2006 Jul;53(7):1425-8. doi: 10.1109/TBME.2006.873684.

Abstract

We present an automated left ventricular (LV) myocardial boundary extraction method. Automatic localization of the LV is achieved using a motion map and an expectation maximization algorithm. The myocardial region is then segmented using an intensity-based fuzzy affinity map and the myocardial contours are extracted by cost minimization through a dynamic programming approach. The results from the automated algorithm compared against the experienced radiologists using Bland and Altman analysis were found to have consistent mean bias of 7% and limits of agreement comparable to the inter-observer variability inherent in the manual method.

Publication types

  • Controlled Clinical Trial

MeSH terms

  • Adult
  • Algorithms*
  • Artificial Intelligence*
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Information Storage and Retrieval / methods
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Stroke Volume
  • Ventricular Dysfunction, Left / diagnosis*