Myocardial Segmentation of Late Gadolinium Enhanced MR Images by Propagation of Contours from Cine MR Images

TL;DR

This paper introduces an automatic framework for segmenting myocardium in LGE cardiac MR images by propagating contours from cine MR images, leveraging shared information and advanced registration techniques.

Contribution

It proposes a novel segmentation method that combines affine and nonrigid registration with local deformation driven by LGE image features, improving accuracy over existing methods.

Findings

Accurate myocardial segmentation achieved on real patient data.

Framework outperforms traditional methods in reliability and precision.

Effective utilization of cine and LGE image correspondence enhances segmentation quality.

Abstract

Automatic segmentation of myocardium in Late Gadolinium Enhanced (LGE) Cardiac MR (CMR) images is often difficult due to the intensity heterogeneity resulting from accumulation of contrast agent in infarcted areas. In this paper, we propose an automatic segmentation framework that fully utilizes shared information between corresponding cine and LGE images of a same patient. Given myocardial contours in cine CMR images, the proposed framework achieves accurate segmentation of LGE CMR images in a coarse-to-fine manner. Affine registration is first performed between the corresponding cine and LGE image pair, followed by nonrigid registration, and finally local deformation of myocardial contours driven by forces derived from local features of the LGE image. Experimental results on real patient data with expert outlined ground truth show that the proposed framework can generate accurate and reliable results for myocardial segmentation of LGE CMR images.