Automated Selection of Standardized Planes from Ultrasound Volume
作者： Bahbibi Rahmatullah , Aris Papageorghiou , J. Alison Noble
DOI: 10.1007/978-3-642-24319-6_5
关键词: Artificial intelligence 、 AdaBoost 、 3D ultrasound 、 Clinical diagnosis 、 Selection (genetic algorithm) 、 Standard plane 、 Computer vision 、 Ultrasound 、 Volume (compression) 、 Fetal biometry 、 Computer science
摘要: The search for the standardized planes in a 3D ultrasound volume is hard and time consuming process even expert physicians. A scheme finding would be beneficial advancing use of volumetric clinical diagnosis. In this paper, we propose new method to automatically select standard plane from fetal application biometry measurement. To our knowledge, first study domain. based on AdaBoost learning algorithm has been evaluated set 30 volumes. experimental results are promising with recall rate 91.29%. We believe will increase accuracy efficiency patient monitoring care management obstetrics, specifically detecting growth restricted fetuses.
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