General Object Reconstruction Based on Simplex Meshes
International Journal of Computer Vision
An approach to 2D/3D registration of a vertebra in 2D X-ray fluoroscopies with 3D CT images
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization
IEEE Transactions on Pattern Analysis and Machine Intelligence
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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.