[Purpose/significance] Ultrasound examination is an important basis for diagnosis, but the major examination data is in the form of text. So, based these data, this paper studies a method that can automatically structure natural language texts and construct knowledge network, which lays the data foundation for further mining clinical knowledge hidden in EMR.[Method/process] This paper improved the application of natural language processing technology in ultrasonic, including three main steps:segmentation processing, content location and structured recognition, to realize the segmentation and labeling of ultrasonic text, and on this basis, the ultrasound examination knowledge network was established.[Result/conclusion] The test results of real data show that the method for structuring ultrasound texts proposed in this paper has better performance. This method can realize the automatic construction of knowledge network of batch ultrasound texts, and can reflect the potential knowledge of hierarchical relationship and attribute structure of structured content in ultrasonic text.
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