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Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI

机译:MRI全心分割的多尺度贴片和多模态图集

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A whole heart segmentation (WHS) method is presented for cardiac MRI. This segmentation method employs multi-modality atlases from MRI and CT and adopts a new label fusion algorithm which is based on the proposed multi-scale patch (MSP) strategy and a new global atlas ranking scheme. MSP, developed from the scale-space theory, uses the information of multi-scale images and provides different levels of the structural information of images for multi-level local atlas ranking. Both the local and global atlas ranking steps use the information theoretic measures to compute the similarity between the target image and the atlases from multiple modalities. The proposed segmentation scheme was evaluated on a set of data involving 20 cardiac MRI and 20 CT images. Our proposed algorithm demonstrated a promising performance, yielding a mean WHS Dice score of 0.899 +/- 0.0340, Jaccard index of 0.818 +/- 0.0549, and surface distance error of 1.09 +/- 1.11 mm for the 20 MRI data. The average runtime for the proposed label fusion was 12.58 min. (C) 2016 Elsevier B.V. All rights reserved.
机译:提出了一种用于心脏MRI的全心分割(WHS)方法。这种分割方法采用了来自MRI和CT的多模式图集,并采用了一种新的标签融合算法,该算法基于提出的多尺度补丁(MSP)策略和新的全局图集排名方案。从比例空间理论发展而来的MSP使用多尺度图像的信息,并为多层局部图集排名提供不同级别的图像结构信息。本地和全局图集排名步骤均使用信息理论方法来从多种模态计算目标图像和图集之间的相似度。在涉及20个心脏MRI和20个CT图像的一组数据上评估了建议的分割方案。我们提出的算法表现出令人鼓舞的性能,对于20个MRI数据,平均WHS Dice得分为0.899 +/- 0.0340,Jaccard指数为0.818 +/- 0.0549,表面距离误差为1.09 +/- 1.11 mm。建议标签融合的平均运行时间为12.58分钟。 (C)2016 Elsevier B.V.保留所有权利。

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