论文标题
对3D和4D医疗图像中左心附件细分和分析的调查
A Survey of Left Atrial Appendage Segmentation and Analysis in 3D and 4D Medical Images
论文作者
论文摘要
心房颤动（AF）是一种心血管疾病，被认为是中风的主要危险因素之一。由于AF引起的大多数中风是由始于左心附属物（LAA）的凝块引起的。 LAA闭塞是降低中风风险的有效程序。使用术前成像和分析计划该程序已显示出好处。分析通常是通过手动在2D切片上的附属物进行分段来完成的。自动LAA细分方法可以节省专家的时间，并提供有见地的3D可视化和准确的自动测量，以帮助进行医疗程序。已经提出了几种半自动和完全自动的方法。本文对3D和4D医学图像的自动LAA分割方法进行了综述，包括CT，MRI和超声心动图图像。我们将方法分类为基于启发式和模型的方法，以及半自动和完全自动的方法。我们总结并比较了提出的方法，评估其有效性，并提出了当前的挑战和克服这些方法的挑战。
Atrial fibrillation (AF) is a cardiovascular disease identified as one of the main risk factors for stroke. The majority of strokes due to AF are caused by clots originating in the left atrial appendage (LAA). LAA occlusion is an effective procedure for reducing stroke risk. Planning the procedure using pre-procedural imaging and analysis has shown benefits. The analysis is commonly done by manually segmenting the appendage on 2D slices. Automatic LAA segmentation methods could save an expert's time and provide insightful 3D visualizations and accurate automatic measurements to aid in medical procedures. Several semi- and fully-automatic methods for segmenting the appendage have been proposed. This paper provides a review of automatic LAA segmentation methods on 3D and 4D medical images, including CT, MRI, and echocardiogram images. We classify methods into heuristic and model-based methods, as well as into semi- and fully-automatic methods. We summarize and compare the proposed methods, evaluate their effectiveness, and present current challenges in the field and approaches to overcome them.
