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On ultrasound classification of stroke risk factors from randomly chosen respondents using non-invasive multispectral ultrasonic brain measurements and adaptive profiles

机译:关于使用非侵入性多光谱超声脑部测量和自适应配置文件从随机选择的受访者中对中风危险因素进行超声分类

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摘要

In this paper, we present a new brain diagnostic method based on a computer aided multispectral ultrasound diagnostics method (CAMUD). We explored the standard values of the relative time of flight (RIT), as well as the attenuation, ATN, of multispectral longitudinal ultrasound waves propagated non-invasively through the brains of a standard Caucasian volunteer population across different ages and genders. For the interpretation of the volunteers health questionnaire and ultrasound data we explored various clustering and classification algorithms, such as PCA and ANOVA. We showed that the RIT and ATN values provide very good estimators of possible physiological changes in the brain tissue and can differentiate the possible high-risk groups obtained by other groups and methods (Russo et al. [1]; Lloyd-Jones et al. [2]; Medscape [3]).
机译:在本文中,我们提出了一种基于计算机辅助多光谱超声诊断方法(CAMUD)的新型大脑诊断方法。我们探讨了相对飞行时间(RIT)的标准值,以及通过不同年龄和性别的白种人自愿志愿者的大脑无创传播的多光谱纵向超声波的衰减ATN。为了解释志愿者的健康调查表和超声数据,我们探索了各种聚类和分类算法,例如PCA和ANOVA。我们发现RIT和ATN值可以很好地估计大脑组织中可能发生的生理变化,并且可以区分通过其他组和方法获得的可能的高风险组(Russo等人[1]; Lloyd-Jones等人。 [2]; Medscape [3])。

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