4D心脏SPAMM图像中左心室和右心室的自动分割。

Albert Montillo, Dimitris Metaxas, Leon Axel
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引用次数: 59

摘要

在本文中,我们描述了一种完全自动的基于体积的方法,用于在4D标记的MR(SPAMM)图像中分割左心室和右心室,用于定量心脏分析。我们使用一种新的基于尺度的模糊连通性程序来校正由表面线圈引起的每个体积中的背景强度变化。我们将3D灰度开口应用于校正后的数据,以创建仅包含血液填充区域的体积。我们通过最小化区域方差或通过自适应统计阈值方法来对体积进行阈值设置。我们使用一种基于空间和时间形状相似性的新方法来分离心室充满血液的区域。我们使用这些区域来定义心内膜轮廓,并使用它们来初始化通过灰度闭合图像的边缘图的梯度矢量流定位心外膜的活动轮廓。给出了正常和患病患者的定量和定性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Segmentation of the Left and Right Ventricles in 4D Cardiac SPAMM Images.

In this paper we describe a completely automated volume-based method for the segmentation of the left and right ventricles in 4D tagged MR (SPAMM) images for quantitative cardiac analysis. We correct the background intensity variation in each volume caused by surface coils using a new scale-based fuzzy connectedness procedure. We apply 3D grayscale opening to the corrected data to create volumes containing only the blood filled regions. We threshold the volumes by minimizing region variance or by an adaptive statistical thresholding method. We isolate the ventricular blood filled regions using a novel approach based on spatial and temporal shape similarity. We use these regions to define the endocardium contours and use them to initialize an active contour that locates the epicardium through the gradient vector flow of an edgemap of a grayscale-closed image. Both quantitative and qualitative results on normal and diseased patients are presented.

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