We derived an automated algorithm for accurately measuring the thalamic diameter from 2D fetal ultrasound (US) brain images. The algorithm overcomes the inherent limitations of the US image modality: non-uniform density, missing boundaries, and strong speckle noise. We introduced a 'guitar' structure that represents the negative space surrounding the thalamic regions. The guitar acts as a landmark for deriving the widest points of the thalamus even when its boundaries are not identifiable. We augmented a generalized level-set framework with a shape prior and constraints derived from statistical shape models of the guitars; this framework was used to segment US images and measure the thalamic diameter. Our segmentation method achieved a higher mean Dice similarity coefficient, Hausdorff distance, specificity and reduced contour leakage when compared to other well-established methods. The automatic thalamic diameter measurement had an inter-observer variability of −0.56±2.29 millimeters compared to manual measurement by an expert sonographer. Our method was capable of automatically estimating the thalamic diameter, with the measurement accuracy on par with clinical assessment. Our method can be used as part of computer-assisted screening tools that automatically measure the biometrics of the fetal thalamus; these biometrics are linked to neuro-developmental outcomes.
Introduction: Australian medical ultrasound started in 1959 with the establishment of the Ultrasonics Institute. Since then the technology has advanced tremendously. We are now not only able to obtain clearer images on high specification ultrasound machines but also on pocket‐sized ultrasound machines that are compact, lightweight and affordable.
Method: The following descriptive review will examine the indication for use of pocket ultrasound machines in different clinical settings as well as provide evidence of its image clarity and accuracy. Potentially eligible studies were sought primarily through searches of the electronic databases PubMed, Medline (1996–Present), Embase (1996–Present) and Cochrane Library.
Conclusion: Pocket ultrasound machines, with appropriate ultrasound knowledge and training, can be incorporated successfully in patient management. The addition of point‐of‐care ultrasound has been shown to improve management recommendations and outcomes.
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