Automated identification of left ventricular borders from spin-echo magnetic resonance images. Experimental and clinical feasibility studies.
Automated identification of left ventricular borders from spin-echo magnetic resonance images. Experimental and clinical feasibility studies.
复制标题
从自旋回波磁共振图像自动识别左心室边界。
DOI：
10.1097/00004424-199104000-00002
复制
发表时间：
1991
影响因子：
6.7
通讯作者：
Skorton,DJ
中科院分区：
文献类型：
--
作者：
Fleagle,SR;Thedens,DR;Ehrhardt,JC;Scholz,TD;Skorton,DJ
门控心脏磁共振成像（MRI）允许详细评价心脏解剖结构，包括计算左心室容积和质量。然而，当前导出该信息的方法需要手动跟踪若干图像中的边界;这种手动方法是繁琐、耗时且主观的。本研究的目的是应用一种新的计算机化方法来自动识别MRI中的心内膜和心外膜边界。作者获得了13个离体动物心脏的系列短轴自旋回波MRI。还获得了11名正常人志愿者的短轴，自旋回波心室图像。提出了一种基于图搜索原理的自动边缘检测方法，并应用于离体和活体图像的边缘检测。根据心内膜和心外膜面积计算左心室质量，并与离体心脏图像的解剖左心室质量进行比较。从计算机导出的边界计算的心内膜和心外膜面积与观察者描记的面积进行比较。在离体心脏的计算机衍生描记和观察者描记（心内膜r= 0.97，心外膜r= 0.99）与体内扫描（心内膜r= 0.92，心外膜r= 0.90）之间存在非常密切的对应关系。在离体心脏中，计算机生成的左心室质量与实际左心室质量之间也有密切的对应关系（r= 0.99）。这些数据表明MRI中自动边缘检测的可行性。虽然需要进一步的验证，这种方法可能被证明是有用的临床MRI。
Gated cardiac magnetic resonance imaging (MRI) permits detailed evaluation of cardiac anatomy, including the calculation of left ventricular volume and mass. Current methods of deriving this information, however, require manual tracing of boundaries in several images; such manual methods are tedious, time consuming, and subjective. The purpose of this study is to apply a new computerized method to automatically identify endocardial and epicardial borders in MRIs. The authors obtained serial, short-axis, spin-echo MRIs of 13 excised animal hearts. Also obtained were selected short-axis, spinecho ventricular images of 11 normal human volunteers. A method of automated edge detection based on graph-searching principles was applied to the ex vivo and in vivo images. Endocardial and epicardial areas were used to compute left ventricular mass and were compared with the anatomic left ventricular mass for the images of excised hearts. The endocardial and epicardial areas calculated from computer-derived borders were compared with areas from observer tracing. There was very close correspondence between computer-derived and observer tracings for excised hearts (r= 0.97 for endocardium, r= 0.99 for epicardium) and in vivo scans (r= 0.92 for endocardium, r= 0.90 for epicardium). There also was aclose correspondence between computer-generated and actual left ventricular mass in the excised hearts (r= 0.99). These data suggest the feasibility of automated edge detection in MRIs. Although further validation is needed, this method may prove useful in clinical MRI.