Abstract
Measurement of the width of fetal lateral ventricles (LVs) in prenatal ultrasound (US) images is essential for antenatal neuronographic assessment. However, the manual measurement of LV width is highly subjective and relies on the clinical experience of scanners. To deal with this challenge, we propose a computer-aided detection framework for automatic measurement of fetal LVs in two-dimensional US images. First, we train a deep convolutional network on 2,400 images of LVs to perform pixel-wise segmentation. Then, the number of pixels per centimeter (PPC), a vital parameter for quantifying the caliper in US images, is obtained via morphological operations guided by prior knowledge. The estimated PPC, upon conversion to a physical length, is used to determine the diameter of the LV by employing the minimum enclosing rectangle method. Extensive experiments on a self-collected dataset demonstrate that the proposed method achieves superior performance over manual measurement, with a mean absolute measurement error of 1.8 mm. The proposed method is fully automatic and is shown to be capable of reducing measurement bias caused by improper US scanning.
Highlights
Ultrasound (US) is widely used in prenatal diagnosis because it is non-radiative, noninvasive, real-time, and inexpensive [1, 2]
The pixels per centimeter (PPC) is obtained from the detected caliper using prior knowledge, and the pixel length of the lateral ventricles (LVs) is obtained by the minimum enclosing rectangle (MER) method
In the case of the 5-caliper, the PPC of the image is the distance between adjacent scales multiplied by 2; for the 10-caliper, the PPC is the distance between adjacent scales
Summary
Ultrasound (US) is widely used in prenatal diagnosis because it is non-radiative, noninvasive, real-time, and inexpensive [1, 2]. Can be diagnosed by measuring the fetal lateral ventricles (LVs) in standard plane images of the fetal brain. Such manual measurement requires extensive and comprehensive clinical knowledge of fetal LVs. such manual measurement requires extensive and comprehensive clinical knowledge of fetal LVs It is a challenging task, especially for novice scanners. The automatic measurement of fetal biometrics—such as head circumference [7, 8] and femur length [9, 10]—has attracted widespread attention in recent years, work on fetal LV measurement is rare
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