Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging.
Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging.
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DOI：
10.1155/2016/2581676
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发表时间：
2016
影响因子：
--
通讯作者：
Hu Q
中科院分区：
文献类型：
--
作者：
Zhang X;Jing S;Gao P;Xue J;Su L;Li W;Ren L;Hu Q
在超急性期分割梗死是具有挑战性的，因为它们表现出很大的可变性，甚至可能很难为专家手动描绘。本文提出了一种基于稀疏表示的分类方法。对于每个患者，四个体积数据项，包括三个体积的扩散加权成像和计算的不对称图提取补丁功能，然后馈送到字典学习和分类的基础上稀疏表示。采用弹性网代替传统的L0-范数/L1-范数对稀疏表示的约束，以稳定稀疏代码。为了降低计算成本并减少假阳性，确定感兴趣区域以限制候选梗死体素。所提出的方法已被验证的98个连续的患者在发病后6小时内招募。实验结果表明，该方法能够较好地处理具有强度变异性和边界模糊的梗死灶，其Dice系数（0.755 ± 0.118）明显高于其他两种方法及其增强版本，并将其分割限制在感兴趣区域内（平均Dice系数小于0.610）。所提出的方法可以提供一个潜在的工具，量化梗死的扩散加权成像在超急性期的准确性和速度，以协助决策，特别是溶栓治疗。
Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L 0-norm/L 1-norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118) than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610). The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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DOI：
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发表时间：
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作者：
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DOI：
10.1016/j.jstrokecerebrovasdis.2006.11.003
发表时间：
2007-03-01
期刊：
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
影响因子：
--
作者：
Rivers, Carly S;Wardlaw, Joanna M;Dennis, Martin S
通讯作者：
Dennis, Martin S