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首页> 外文期刊>Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society >Automatic detection and quantification of brain midline shift using anatomical marker model
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Automatic detection and quantification of brain midline shift using anatomical marker model

机译:使用解剖标记模型自动检测和量化脑中线移位

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摘要

Brain midline shift (MLS) is a significant factor in brain CT diagnosis. In this paper, we present a new method of automatically detecting and quantifying brain midline shift in traumatic injury brain CT images. The proposed method automatically picks out the CT slice on which midline shift can be observed most clearly and uses automatically detected anatomical markers to delineate the deformed midline and quantify the shift. For each anatomical marker, the detector generates five candidate points. Then the best candidate for each marker is selected based on the statistical distribution of features characterizing the spatial relationships among the markers. Experiments show that the proposed method outperforms previous methods, especially in the cases of large intra-cerebral hemorrhage and missing ventricles. A brain CT retrieval system is also developed based on the brain midline shift quantification results.
机译:脑中线移位(MLS)是脑CT诊断的重要因素。在本文中,我们提出了一种自动检测和量化创伤性颅脑CT图像中脑中线移位的新方法。所提出的方法自动挑选出可以最清楚地观察到中线偏移的CT切片,并使用自动检测到的解剖标记来描绘变形的中线并量化偏移。对于每个解剖标记,检测器会生成五个候选点。然后,基于表征标记之间空间关系的特征的统计分布,为每个标记选择最佳候选者。实验表明,所提出的方法优于以前的方法,特别是在脑内大出血和脑室缺失的情况下。还基于大脑中线移位量化结果开发了大脑CT检索系统。

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