Myocardial Segmentation of Late Gadolinium Enhanced MR Images by Propagation of Contours from Cine MR Images
This work addresses a domain-specific challenge in medical imaging for cardiac analysis, offering an incremental improvement by leveraging shared information between image types.
The paper tackles the problem of automatic myocardial segmentation in Late Gadolinium Enhanced (LGE) Cardiac MR images, which is difficult due to intensity heterogeneity from contrast agent accumulation, by proposing a framework that propagates contours from corresponding cine images using registration and local deformation, achieving accurate and reliable results as validated on real patient data with expert ground truth.
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.