Abstract
The search for the standardized planes in a 3D ultrasound volume is a hard and time consuming process even for expert physicians. A scheme for finding the standardized planes would be beneficial in advancing the use of volumetric ultrasound for clinical diagnosis. In this paper, we propose a new method to automatically select the standard plane from the fetal ultrasound volume for the application of fetal biometry measurement. To our knowledge, this is the first study in the fetal ultrasound domain. The method is based on the AdaBoost learning algorithm and has been evaluated on a set of 30 volumes. The experimental results are promising with a recall rate of 91.29%. We believe this will increase the accuracy and efficiency in patient monitoring and care management in obstetrics, specifically in detecting growth restricted fetuses.
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Rahmatullah, B., Papageorghiou, A., Noble, J.A. (2011). Automated Selection of Standardized Planes from Ultrasound Volume. In: Suzuki, K., Wang, F., Shen, D., Yan, P. (eds) Machine Learning in Medical Imaging. MLMI 2011. Lecture Notes in Computer Science, vol 7009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24319-6_5
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DOI: https://doi.org/10.1007/978-3-642-24319-6_5
Publisher Name: Springer, Berlin, Heidelberg
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