Calibration of ultrasound scanners for surface impedance measurement
The primary objective of this research was to investigate the feasibility of calibrating ultrasound scanners to measure surface impedance from reflection data. The method proposed uses calibration curves from known impedance interfaces. This plot, or calibration curve, may then be used, with interpolation, to relate measured grey level to impedance for the characterization of tissue specimens with unknown properties. This approach can be used independent of different medical ultrasound scanner systems to solve for reproducible tissue impedance values without offline data processing and complicated custom electronics. Two medical ultrasound machines from different manufacturers were used in the experiment; a 30 MHz and a 7.5 MHz machine. The calibration curves for each machine were produced by imaging the interfaces of a vegetable oil floating over varying salt solutions. To test the method, porcine liver, kidney, and spleen acoustical impedances were determined by relating measured grey levels to reflection coefficients using calibration curves and then inverting the reflection coefficients to obtain impedance values. The 30 MHz ultrasound machine’s calculated tissue impedances for liver, kidney, and spleen were 1.476 ± 0.020, 1.486 ± 0.020, 1.471 ± 0.020 MRayles respectively. The 7.5 MHz machine’s tissue impedances were 1.467 ± 0.088, 1.507 ± 0.088, and 1.457 ± 0.088 MRayles respectively for liver, kidney and spleen. The differences between the two machines are 0.61%, 1.41%, and 0.95% for the impedance of liver, kidney, and spleen tissue, respectively. If the grey level is solely used to characterize the tissue, then the differences are 45.9%, 40.3%, and 39.1% for liver, kidney, and spleen between the two machines. The results support the hypothesis that tissue impedance can be determined using calibration curves and be consistent between multiple machines.
Inverse Problem, Calibration, Tissue Characterization, Ultrasonography, Tissue Impedance
Master of Science (M.Sc.)