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首页> 外文期刊>Medical and Biological Engineering and Computing: Journal of the International Federation for Medical and Biological Engineering >Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations
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Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations

机译:用于检测创伤性颅内出血的微波技术:对软硬质血肿和数值模拟的幻像测试

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摘要

Traumatic brain injury is the leading cause of death and severe disability for young people and a major public health problem for elderly. Many patients with intracranial bleeding are treated too late, because they initially show no symptoms of severe injury and are not transported to a trauma center. There is a need for a method to detect intracranial bleedings in the prehospital setting. In this study, we investigate whether broadband microwave technology (MWT) in conjunction with a diagnostic algorithm can detect subdural hematoma (SDH). A human cranium phantom and numerical simulations of SDH are used. Four phantoms with SDH 0, 40, 70 and 110 mL are measured with a MWT instrument. The simulated dataset consists of 1500 observations. Classification accuracy is assessed using fivefold cross-validation, and a validation dataset never used for training. The total accuracy is 100 and 82-96 % for phantom measurements and simulated data, respectively. Sensitivity and specificity for bleeding detection were 100 and 96 %, respectively, for the simulated data. SDH of different sizes is differentiated. The classifier requires training dataset size in order of 150 observations per class to achieve high accuracy. We conclude that the results indicate that MWT can detect and estimate the size of SDH. This is promising for developing MWT to be used for prehospital diagnosis of intracranial bleedings.
机译:创伤性脑损伤是年轻人死亡和严重残疾的主要原因和老年人的主要公共卫生问题。许多颅内出血的患者被治疗得太晚,因为它们最初显示出严重损伤的症状,并且不会被运输到创伤中心。需要一种检测在预孢子环境中的颅内出血的方法。在这项研究中,我们研究了宽带微波技术(MWT)是否与诊断算法结合可以检测软骨血肿(SDH)。使用人的颅骨幻影和SDH的数值模拟。用MWT仪器测量具有SDH 0,40,70和110mL的四个幻影。模拟数据集由1500个观察组成。使用五倍交叉验证评估分类准确度,并且从未用于培训的验证数据集。幻像测量和模拟数据的总精度分别为100和82-96%。对于模拟数据,出血检测的敏感性和特异性分别为100和96%。不同尺寸的SDH是区分的。分类器需要每个类的150个观察顺序训练数据集大小以实现高精度。我们得出结论,结果表明MWT可以检测和估计SDH的大小。这是开发MWT用于颅内出血的先前诊断。

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