利用心脏CT图像分割左心耳的方法

Itaru Takayashiki, A. Doi, Toru Kato, H. Takahashi, Shoto Sekimura, M. Hozawa, Y. Morino
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引用次数: 1

摘要

本研究提出了一种从心脏CT图像中自动提取左心耳区域细节的方法,以便于左心耳闭塞术的术前规划。由于心脏是一个非常复杂的器官,通常很难在CT图像中自动分类左心耳区域。因此,除了使用全卷积神经网络的分割方法外,我们还使用mini-batch和对抗训练对左心房附件区域进行了自动提取。该方法应用于用造影剂制作的心脏CT图像。通过该方法,可以从心脏CT图像中自动获取左心耳闭合术前规划支持所需的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method for left atrial appendage segmentation using heart CT images
In this study, we propose a method to automatically extract the details of the left atrial appendage region from heart CT images in order to facilitate the preoperative planning of Left Atrial Appendage Occlusion. Generally, it is difficult to automatically classify the left atrial appendage region in a heart CT image because the heart is a very complicated organ. Therefore, in addition to the segmentation method using fully convolutional neural networks, we performed an automatic extraction of only the left atrial appendage region using mini-batch and adversarial training. This method was applied to heart CT images made with a contrast medium. With this method, it becomes possible to automatically obtain information necessary for preoperative planning support of left atrial appendage closure from heart CT images.
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