- Poster presentation
- Open Access
Automatic myocardium segmentation of LGE MRI by deformable models with prior shape data
© Lu et al; licensee BioMed Central Ltd. 2013
- Published: 30 January 2013
- Late Gadolinium Enhancement
- Deformable Model
- Late Gadolinium Enhancement Image
- Deformable Contour
- Epicardial Contour
Previously a myocardial tissue classification algorithm has been developed to locate and quantify infarct in a given myocardial region-of-interest specified on late gadolinium enhancement (LGE) MR images . To complete the automation requires an endocardial and epicardial contour detection algorithm to replace the current practice of manual contouring that is time-consuming and subject to intra- and inter-observer variability. Challenges include: 1) the intensity inhomogeneity of both the healthy and infarct myocardium; 2) the existence of an infarct on a given slice is not known a priori; 3) a sub-endocardial infarct region's boundary can be easily mistaken for the endocardial contour due to the proximity and strength of the edge (gradient); and 4) incorporating prior anatomical information (e.g., cine steady-state free precession (SSFP) MRI) while allowing for possible motion between separate studies.
Our method provides a high degree of automation and accuracy. The results for the proposed automated segmentation technique indicate that it will streamline accurate quantification of myocardial infarct on LGE MR infarct images in clinical practice.
MaRS Innovation 2011 Medical Sciences Competitive Proof of Principle (MSCPoP) for Medical Devices and Ontario Research Fund, (Imaging for Cardiovascular Therapeutics)
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