Wei Dong, Sun Ying, Chai Ping, Low Adrian, Ong Sim Heng
Department of Electrical and Computer Engineering, National University of Singapore, Singapore.
Med Image Comput Comput Assist Interv. 2011;14(Pt 3):428-35. doi: 10.1007/978-3-642-23626-6_53.
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.
由于梗死区域中造影剂的积聚导致强度异质性，钆延迟增强（LGE）心脏磁共振成像（CMR）中心肌的自动分割通常很困难。在本文中，我们提出了一个自动分割框架，该框架充分利用了同一患者相应电影图像和LGE图像之间的共享信息。给定电影CMR图像中的心肌轮廓，所提出的框架以粗到细的方式实现了LGE CMR图像的精确分割。首先在相应的电影图像和LGE图像对之间进行仿射配准，然后进行非刚性配准，最后由LGE图像的局部特征导出的力驱动心肌轮廓的局部变形。对具有专家勾勒的地面真值的真实患者数据的实验结果表明，所提出的框架可以为LGE CMR图像的心肌分割生成准确可靠的结果。
