Automatic Cardiac LV Segmentation in MRI Using Modified Graph Cuts with Smoothness and Interslice Constraints

作者：Alba Xenia^*; Figueras i Ventura Rosa M; Lekadir Karim; Tobon Gomez Catalina; Hoogendoorn Corne; Frangi Alejandro F

来源：Magnetic Resonance in Medicine, 2014, 72(6): 1775-1784.

DOI：10.1002/mrm.25079

• magnetic resonance imaging
• late-enhanced magnetic resonance imaging
• cardiac
• myocardial segmentation
• graph cut

PurposeMagnetic resonance imaging (MRI), specifically late-enhanced 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. %26lt;br%26gt;MethodsA 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. %26lt;br%26gt;ResultsThe 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 0.810.05 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. %26lt;br%26gt;ConclusionThe experimental validation with two magnetic resonance sequences demonstrates increased accuracy and versatility. Magn Reson Med 72:1775-1784, 2014.

• 出版日期2014-12