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Database guided detection of anatomical landmark points in 3D images of the heart

机译：心脏三维图像解剖标志点的数据库引导检测

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摘要

Automated landmark detection may prove invaluable in the analysis of real-time three-dimensional (3D) echocardiograms. By detecting 3D anatomical landmark points, the standard anatomical views can be extracted automatically in apically acquired 3D ultrasound images of the left ventricle, for better standardization of visualization and objective diagnosis. Furthermore, the landmarks can serve as an initialization for other analysis methods, such as segmentation. The described algorithm applies landmark detection in perpendicular planes of the 3D dataset. The landmark detection exploits a large database of expert annotated images, using an extensive set of Haar features for fast classification. The detection is performed using two cascades of Adaboost classifiers in a coarse to fine scheme. The method is evaluated by measuring the distance of detected and manually indicated landmark points in 25 patients. The method can detect landmarks accurately in the four-chamber (apex: 7.9±7.1mm, septal mitral valve point: 5.6±2.7mm; lateral mitral valve point: 4.0±2.6mm) and two-chamber view (apex: 7.1±6.7mm, anterior mitral valve point: 5.8±3.5mm, inferior mitral valve point: 4.5±3.1mm). The results compare well to those reported by others.
机译：自动化地标检测可能在实时三维（3D）超声心动图的分析中可以证明是无价的。通过检测3D解剖地标点，可以在左心室的3D超声图像中自动提取标准解剖视图，以便更好地标准化可视化和客观诊断。此外，该地标可以用作其他分析方法的初始化，例如分段。所描述的算法在3D数据集的垂直平面中应用地标检测。该地标检测利用了一个大型专家数据库，使用广泛的HAAR功能进行了快速分类。通过粗略到精细方案，使用两个级联的Adaboost分类器进行检测。通过测量25名患者中检测到和手动指示的地标点的距离来评估该方法。该方法可以在四室精确地检测地标（顶点：7.9±7.1mm，隔膜二瓣点：5.6±2.7mm;横向二尖瓣点：4.0±2.6mm）和两个腔室视图（Apex：7.1±6.7 MM，前二尖瓣点：5.8±3.5mm，较差二尖瓣点：4.5±3.1mm）。结果比其他人报告的结果相比。

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