Automatic cardiac LV Segmentation in MRI using modified graph cuts with smoothness and interslice constraints

Xènia Albà, Rosa M. Figueras I Ventura, Karim Lekadir, Catalina Tobon-Gomez, Corné Hoogendoorn, Alejandro F. Frangi

Research output: Contribution to journalArticlepeer-review


Purpose: Magnetic resonance imaging (MRI), specifically lateenhanced MRI, is the standard clinical imaging protocol to assess cardiac viability. Segmentation of myocardial walls is a prerequisite for this assessment. Automatic and robust multisequence segmentation is required to support processing massive quantities of data.

Conclusion: The experimental validation with two magnetic resonance sequences demonstrates increased accuracy and versatility.

Methods: A generic rule-based framework to automatically segment the left ventricle myocardium is presented here. We use intensity information, and include shape and interslice smoothness constraints, providing robustness to subject- and study-specific changes. Our automatic initialization considers the geometrical and appearance properties of the left ventricle, as well as interslice information. The segmentation algorithm uses a decoupled, modified graph cut approach with control points, providing a good balance between flexibility and robustness.

Results: The method was evaluated on late-enhanced MRI images from a 20-patient in-house database, and on cine-MRI images from a 15-patient open access database, both using as reference manually delineated contours. Segmentation agreement, measured using the Dice coefficient, was 0:81 ± 0:05 and 0:92±0:04 for late-enhanced MRI and cine-MRI, respectively. The method was also compared favorably to a three-dimensional Active Shape Model approach.

Original languageEnglish
Pages (from-to)1775-1784
Number of pages10
JournalMagnetic Resonance in Medicine
Issue number6
Publication statusPublished - 1 Dec 2014


  • Cardiac
  • Graph cut
  • Late-enhanced magnetic resonance imaging
  • Magnetic resonance imaging
  • Myocardial segmentation


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