|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
DYNAMIC RESOLUTION SELECTION IN ULTRASONIC STRAIN IMAGING
Joel E. Lindop, Graham M. Treece, Andrew H. Gee and Richard W. Prager
Ultrasonic strain imaging promises to be a valuable tool in medical diagnostics. Reliability and ease-of-use have become important considerations. These depend on selection of appropriate imaging parameters. Two tasks are undertaken here. The tradeoff between resolution and estimation precision is examined closely to establish models for the relationships with imaging parameters and data properties. These models are then applied in a system that automatically sets the imaging parameters responsive to the data quality and the required estimation precision, so as to produce more meaningful images under varying scan conditions. The new system is applied to simulation, in vitro and in vivo data for validation. It reduces the complexity of the sonographer's role in strain imaging, and produces images of reliable quality even when the level of signal decorrelation varies throughout the ultrasound data.
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