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A Semi-Automatic Method To Segment The Left Atrium in MR Volumes With Varying Slice Numbers

机译:具有不同切片数的MR容积中的左心房分割的半自动方法

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Atrial fibrillation (AF) is the most common sustained arrhythmia and is associated with dramatic increases in mortality and morbidity. Atrial cine MR images are increasingly used in the management of this condition, but there are few specific tools to aid in the segmentation of such data. Some characteristics of atrial cine MR (thick slices, variable number of slices in a volume) preclude the direct use of traditional segmentation tools. When combined with scarcity of labelled data and similarity of the intensity and texture of the left atrium (LA) to other cardiac structures, the segmentation of the LA in CINE MRI becomes a difficult task. To deal with these challenges, we propose a semi-automatic method to segment the left atrium (LA) in MR images, which requires an initial user click per volume. The manually given location information is used to generate a chamber location map to roughly locate the LA, which is then used as an input to a deep network with slightly over 0.5 million parameters. A tracking method is introduced to pass the location information across a volume and to remove unwanted structures in segmentation maps. According to the results of our experiments conducted in an in-house MRI dataset, the proposed method outperforms the U-Net [1] with a margin of 20 mm on Hausdorff distance and 0.17 on Dice score, with limited manual interaction.
机译:心房颤动(AF)是最常见的持续性心律不齐,并与死亡率和发病率急剧增加有关。在这种情况的管理中越来越多地使用心房电影MR图像,但是很少有特定工具可以帮助分割此类数据。心房MR的某些特征(厚切片,体积中切片数量可变)使得无法直接使用传统的分割工具。当与标记数据的缺乏以及左心房(LA)的强度和纹理与其他心脏结构的相似性相结合时,在CINE MRI中将LA分割成为一项艰巨的任务。为了应对这些挑战,我们提出了一种半自动方法来分割MR图像中的左心房(LA),这需要用户对每个体积进行初始点击。手动提供的位置信息用于生成腔室位置图以粗略地定位LA,然后将其用作具有略微超过50万个参数的深层网络的输入。引入了一种跟踪方法,以使位置信息跨整个卷传递,并去除分段图中不需要的结构。根据我们在内部MRI数据集中进行的实验结果,提出的方法优于U-Net [1],在Hausdorff距离上的边距为20 mm,在Dice评分上的边距为0.17,手动交互作用有限。

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