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MA-SOCRATIS:一种用于左心室和疤痕自动稳健分割的流水线。

MA-SOCRATIS: An automatic pipeline for robust segmentation of the left ventricle and scar.

机构信息

Insigneo Institute for In-Silico Medicine, University of Sheffield, Sheffield, UK; Department of Computer Science, University of Sheffield, Regent Court, Sheffield S1 4DP, UK.

Department of Cardiology, Sheffield Teaching Hospitals NHS Trust, Sheffield S5 7AU, UK.

出版信息

Comput Med Imaging Graph. 2021 Oct;93:101982. doi: 10.1016/j.compmedimag.2021.101982. Epub 2021 Aug 26.

Abstract

Multi-atlas segmentation of cardiac regions and total infarct scar (MA-SOCRATIS) is an unsupervised automatic pipeline to segment left ventricular myocardium and scar from late gadolinium enhanced MR images (LGE-MRI) of the heart. We implement two different pipelines for myocardial and scar segmentation from short axis LGE-MRI. Myocardial segmentation has two steps; initial segmentation and re-estimation. The initial segmentation step makes a first estimate of myocardium boundaries by using multi-atlas segmentation techniques. The re-estimation step refines the myocardial segmentation by a combination of k-means clustering and a geometric median shape variation technique. An active contour technique determines the unhealthy and healthy myocardial wall. The scar segmentation pipeline is a combination of a Rician-Gaussian mixture model and full width at half maximum (FWHM) thresholding, to determine the intensity pixels in scar regions. Following this step a watershed method with an automatic seed-points framework segments the final scar region. MA-SOCRATIS was evaluated using two different datasets. In both datasets ground truths were based on manual segmentation of short axis images from LGE-MRI scans. The first dataset included 40 patients from the MS-CMRSeg 2019 challenge dataset (STACOM at MICCAI 2019). The second is a collection of 20 patients with scar regions that are challenging to segment. MA-SOCRATIS achieved robust and accurate performance in automatic segmentation of myocardium and scar regions without the need of training or tuning in both cohorts, compared with state-of-the-art techniques (intra-observer and inter observer myocardium segmentation: 81.9% and 70% average Dice value, and scar (intra-observer and inter observer segmentation: 70.5% and 70.5% average Dice value).

摘要

多图谱分割心脏区域和总梗死瘢痕(MA-SOCRATIS)是一种无监督的自动流水线,用于从心脏的钆延迟增强磁共振图像(LGE-MRI)中分割左心室心肌和瘢痕。我们实现了两种用于短轴 LGE-MRI 心肌和瘢痕分割的不同流水线。心肌分割有两个步骤;初始分割和重新估计。初始分割步骤通过使用多图谱分割技术对心肌边界进行首次估计。重新估计步骤通过 k-均值聚类和几何中位数形状变化技术的组合来细化心肌分割。主动轮廓技术确定不健康和健康的心肌壁。瘢痕分割流水线是瑞利-高斯混合模型和全宽半最大值(FWHM)阈值的组合,用于确定瘢痕区域的强度像素。在此步骤之后,采用分水岭方法和自动种子点框架分割最终的瘢痕区域。MA-SOCRATIS 使用两个不同的数据集进行了评估。在两个数据集,ground truth 都是基于 LGE-MRI 扫描的短轴图像的手动分割。第一个数据集包括来自 MS-CMRSeg 2019 挑战赛数据集(MICCAI 2019 上的 STACOM)的 40 名患者。第二个是一组 20 名具有挑战性的瘢痕区域的患者。与最先进的技术相比,MA-SOCRATIS 在无需培训或调整的情况下,在两个队列中均实现了心肌和瘢痕区域的自动分割的稳健和准确性能(观察者内和观察者间心肌分割:81.9%和 70%的平均 Dice 值,瘢痕(观察者内和观察者间分割:70.5%和 70.5%的平均 Dice 值)。

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