Constantinidès Constantin, Roullot Elodie, Lefort Muriel, Frouin Frédérique
Inserm at University Pierre et Marie Curie, Paris, France.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:3207-10. doi: 10.1109/EMBC.2012.6346647.
A fully automated segmentation method of the left ventricle from short-axis cardiac MR images is proposed and evaluated. The segmentation is based on morphological filtering and gradient vector flow snake for which an automatic setting of parameters has already been proposed. The present work focuses on the automatic detection of a region of interest (ROI) surrounding the left ventricle, prior to the segmentation step. The whole process was applied to the MICCAI 2009 Left Ventricle Challenge database containing 45 subjects (9 healthy subjects and 36 with pathology). The automatic detection of the ROI was judged accurate in 86% of the cases. It failed in 2% of the slices and provided an overestimation in 9% of the slices. Furthermore, the endocardial segmentation was accurate in 80% of the slices and the epicardial was judged satisfactory in 71% of the slices. This fully automated procedure can thus be used as a first step in a user controlled approach, in order to reduce the total number of interactions.
提出并评估了一种从短轴心脏磁共振图像中全自动分割左心室的方法。该分割基于形态学滤波和梯度向量流蛇算法，此前已有人提出了该算法参数的自动设置方法。目前的工作重点是在分割步骤之前自动检测左心室周围的感兴趣区域（ROI）。整个过程应用于包含45名受试者（9名健康受试者和36名患有疾病的受试者）的MICCAI 2009左心室挑战数据库。在86%的病例中，ROI的自动检测被判定为准确。在2%的切片中检测失败，在9%的切片中出现高估。此外，心内膜分割在80%的切片中准确，心外膜在71%的切片中被判定为满意。因此，这种全自动程序可以用作用户控制方法的第一步，以减少交互的总数。
