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Automated Gestational Age Estimation for Monitoring Fetal Growth

机译:用于监测胎儿生长的自动妊娠年龄估计

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Gestation is defined as a period of time between conception and birth. Estimation of gestational age is necessary in order to predict the early date of delivery and monitor the growth of fetus throughout the three trimester of pregnancy. Assessment of gestational age is based on measurement of various fetal biometric parameters like gestational sac, bi-parietal diameter, femur length, abdominal circumference, head circumference during the gestation period. In medical image processing, ultrasound technique plays an important role for imaging organs for an obstetrician and gynecologist. Monitoring of these parameters is done with human interaction. These methods are responsible for multiple subjective decisions which increase the inter-observer error. The main objective of this work is to measure fetal biometric parameter for accurate estimation of gestational age. An automated computer based algorithm has been used to apply morphological operation in order to recognize the desired parameter contour in the ultrasound image, refine its shape and compensate for distinct irregularities, then correctly measure its length, attaining optimum accuracy and reproducibility of measurements. Automation algorithm utilizes morphological operation, Hough transform and tracing methods. It has been found that, the proposed scheme, is able to estimate the gestational age of the fetus with a prediction accuracy of ±2 days.
机译:妊娠定义为从受孕到出生之间的一段时间。估计胎龄是必要的,以便预测分娩的早期日期并监测整个妊娠三个月中胎儿的生长。胎龄的评估基于各种胎儿生物特征参数的测量,例如胎囊,双顶径,股骨长度,腹围,头围。在医学图像处理中,超声技术对妇产科医生的器官成像起着重要作用。这些参数的监视是通过人机交互来完成的。这些方法负责多个主观决策,从而增加了观察者之间的错误。这项工作的主要目的是测量胎儿的生物特征参数,以准确估算胎龄。已经使用基于计算机的自动算法来进行形态学运算,以便识别超声图像中所需的参数轮廓,完善其形状并补偿明显的不规则性,然后正确地测量其长度,从而获得最佳的测量精度和可重复性。自动化算法利用形态学运算,霍夫变换和跟踪方法。已经发现,所提出的方案能够以±2天的预测精度来估计胎儿的胎龄。

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